Index (MOA: Massive Online Analysis 2014.05-SNAPSHOT API)

A B C D E F G H I J K L M N O P Q R S T U V W X Y _

A

AbruptChangeGenerator - Class in moa.streams.generators.cd
AbruptChangeGenerator() - Constructor for class moa.streams.generators.cd.AbruptChangeGenerator
AbstractAMRules - Class in moa.classifiers.rules
AbstractAMRules() - Constructor for class moa.classifiers.rules.AbstractAMRules
AbstractC - Class in moa.clusterers.outliers.AbstractC
AbstractC() - Constructor for class moa.clusterers.outliers.AbstractC.AbstractC
AbstractCBase - Class in moa.clusterers.outliers.AbstractC
AbstractCBase() - Constructor for class moa.clusterers.outliers.AbstractC.AbstractCBase
AbstractChangeDetector - Class in moa.classifiers.core.driftdetection: Abstract Change Detector.
AbstractChangeDetector() - Constructor for class moa.classifiers.core.driftdetection.AbstractChangeDetector
AbstractClassifier - Class in moa.classifiers: Abstract Classifier.
AbstractClassifier() - Constructor for class moa.classifiers.AbstractClassifier: Creates an classifier and setups the random seed option if the classifier is randomizable.
AbstractClassOption - Class in moa.options: Abstract class option.
AbstractClassOption(String, char, String, Class<?>, String) - Constructor for class moa.options.AbstractClassOption: Creates a new instance of an abstract option given its class name, command line interface text, its purpose, its class type and its default command line interface text.
AbstractClassOption(String, char, String, Class<?>, String, String) - Constructor for class moa.options.AbstractClassOption: Creates a new instance of an abstract option given its class name, command line interface text, its purpose, its class type, default command line interface text, and its null text.
AbstractClusterer - Class in moa.clusterers
AbstractClusterer() - Constructor for class moa.clusterers.AbstractClusterer
AbstractConceptDriftGenerator - Class in moa.streams.generators.cd
AbstractConceptDriftGenerator() - Constructor for class moa.streams.generators.cd.AbstractConceptDriftGenerator
AbstractErrorWeightedVote - Class in moa.classifiers.rules.core.voting: AbstractErrorWeightedVote class for weighted votes based on estimates of errors.
AbstractErrorWeightedVote() - Constructor for class moa.classifiers.rules.core.voting.AbstractErrorWeightedVote
AbstractMacroClusterer - Class in moa.clusterers.macro
AbstractMacroClusterer() - Constructor for class moa.clusterers.macro.AbstractMacroClusterer
AbstractMOAObject - Class in moa: Abstract MOA Object.
AbstractMOAObject() - Constructor for class moa.AbstractMOAObject
AbstractOption - Class in moa.options: Abstract option.
AbstractOption(String, char, String) - Constructor for class moa.options.AbstractOption: Creates a new instance of an abstract option given its class name, command line interface text and its purpose.
AbstractOptionHandler - Class in moa.options: Abstract Option Handler.
AbstractOptionHandler() - Constructor for class moa.options.AbstractOptionHandler
AbstractRecommenderData - Class in moa.recommender.rc.data
AbstractRecommenderData() - Constructor for class moa.recommender.rc.data.AbstractRecommenderData
AbstractStreamFilter - Class in moa.streams.filters: Abstract Stream Filter.
AbstractStreamFilter() - Constructor for class moa.streams.filters.AbstractStreamFilter
AbstractTabPanel - Class in moa.gui: Abstract Tab Panel.
AbstractTabPanel() - Constructor for class moa.gui.AbstractTabPanel
AbstractTask - Class in moa.tasks: Abstract Task.
AbstractTask() - Constructor for class moa.tasks.AbstractTask
acc1 - Variable in class moa.gui.TaskTextViewerPanel
acc2 - Variable in class moa.gui.TaskTextViewerPanel
accept(File) - Method in class moa.gui.FileExtensionFilter
accumulatedError - Variable in class moa.classifiers.rules.functions.Perceptron
Accuracy - Class in moa.evaluation
Accuracy() - Constructor for class moa.evaluation.Accuracy
accuracyBaseLearner - Variable in class moa.classifiers.active.ActiveClassifier
AccuracyUpdatedEnsemble - Class in moa.classifiers.meta: The revised version of the Accuracy Updated Ensemble as proposed by Brzezinski and Stefanowski in "Reacting to Different Types of Concept Drift: The Accuracy Updated Ensemble Algorithm", IEEE Trans.
AccuracyUpdatedEnsemble() - Constructor for class moa.classifiers.meta.AccuracyUpdatedEnsemble
AccuracyWeightedEnsemble - Class in moa.classifiers.meta: The Accuracy Weighted Ensemble classifier as proposed by Wang et al.
AccuracyWeightedEnsemble() - Constructor for class moa.classifiers.meta.AccuracyWeightedEnsemble
actionPerformed(ActionEvent) - Method in class moa.gui.clustertab.ClusteringAlgoPanel
actionPerformed(ActionEvent) - Method in class moa.gui.clustertab.ClusteringVisualTab
actionPerformed(ActionEvent) - Method in class moa.gui.outliertab.OutlierAlgoPanel
actionPerformed(ActionEvent) - Method in class moa.gui.outliertab.OutlierVisualTab
actionPerformed(ActionEvent) - Method in class moa.gui.TaskTextViewerPanel
actionPerformed(ActionEvent) - Method in class moa.gui.visualization.RunOutlierVisualizer
actionPerformed(ActionEvent) - Method in class moa.gui.visualization.RunVisualizer
activateLearningNode(HoeffdingOptionTree.InactiveLearningNode, HoeffdingOptionTree.SplitNode, int) - Method in class moa.classifiers.trees.HoeffdingOptionTree
activateLearningNode(HoeffdingTree.InactiveLearningNode, HoeffdingTree.SplitNode, int) - Method in class moa.classifiers.trees.HoeffdingTree
ActiveClassifier - Class in moa.classifiers.active: Active learning setting for evolving data streams.
ActiveClassifier() - Constructor for class moa.classifiers.active.ActiveClassifier
activeLeafByteSizeEstimate - Variable in class moa.classifiers.trees.HoeffdingOptionTree
activeLeafByteSizeEstimate - Variable in class moa.classifiers.trees.HoeffdingTree
activeLeafByteSizeEstimate - Variable in class moa.classifiers.trees.ORTO
activeLeafNodeCount - Variable in class moa.classifiers.trees.HoeffdingOptionTree
activeLeafNodeCount - Variable in class moa.classifiers.trees.HoeffdingTree
activeLearningStrategyOption - Variable in class moa.classifiers.active.ActiveClassifier
actualClassStatistics - Variable in class moa.classifiers.rules.RuleClassification
acuityOption - Variable in class moa.clusterers.CobWeb
ADACC - Class in moa.classifiers.meta: Anticipative and Dynamic Adaptation to Concept Changes.
ADACC() - Constructor for class moa.classifiers.meta.ADACC
AdaHoeffdingOptionTree - Class in moa.classifiers.trees: Adaptive decision option tree for streaming data with adaptive Naive Bayes classification at leaves.
AdaHoeffdingOptionTree() - Constructor for class moa.classifiers.trees.AdaHoeffdingOptionTree
AdaHoeffdingOptionTree.AdaLearningNode - Class in moa.classifiers.trees
AdaHoeffdingOptionTree.AdaLearningNode(double[]) - Constructor for class moa.classifiers.trees.AdaHoeffdingOptionTree.AdaLearningNode
Adaptable - Variable in class moa.classifiers.trees.ORTO
Adaptable - Variable in class moa.classifiers.trees.ORTO.Node
add(CFCluster) - Method in class moa.cluster.CFCluster
add(Cluster) - Method in class moa.cluster.Clustering: add a cluster to the clustering
add(CFCluster) - Method in class moa.clusterers.clustream.ClustreamKernel
add(ClusKernel) - Method in class moa.clusterers.clustree.ClusKernel: Adds the given cluster to this cluster, without making this cluster older.
add(Entry) - Method in class moa.clusterers.clustree.Entry: Add the data cluster of another entry to the data cluster of this entry.
add(DATA) - Method in class moa.clusterers.outliers.utils.mtree.MTree: Adds and indexes a data object.
add(int, T) - Method in class moa.core.AutoExpandVector
add(T) - Method in class moa.core.AutoExpandVector
add(Instance) - Method in class moa.core.InstancesHeader
add(double) - Method in class moa.evaluation.EWMAClassificationPerformanceEvaluator.Estimator
add(double) - Method in class moa.evaluation.FadingFactorClassificationPerformanceEvaluator.Estimator
add(double) - Method in class moa.evaluation.WindowClassificationPerformanceEvaluator.Estimator
add(double) - Method in class moa.evaluation.WindowRegressionPerformanceEvaluator.Estimator
addAll(Collection<? extends T>) - Method in class moa.core.AutoExpandVector
addAll(int, Collection<? extends T>) - Method in class moa.core.AutoExpandVector
addButtonActionListener(ActionListener) - Method in class moa.gui.clustertab.ClusteringSetupTab
addButtonActionListener(ActionListener) - Method in class moa.gui.outliertab.OutlierSetupTab
addChangeListener(ChangeListener) - Method in class moa.gui.ClassOptionEditComponent: Adds the listener to the internal set of listeners.
addChangeListener(ChangeListener) - Method in class moa.gui.ClassOptionWithNamesEditComponent: Adds the listener to the internal set of listeners.
addClusterChangeListener(ClusterEventListener) - Method in class moa.streams.clustering.RandomRBFGeneratorEvents: Add a listener
addedPermanent - Variable in class moa.classifiers.meta.ADACC: Number of added snapshots
addEmptyValue(int) - Method in class moa.evaluation.MeasureCollection
addEntry(Entry, long) - Method in class moa.clusterers.clustree.Node: Add a new Entry to this node.
addEventType(String) - Method in class moa.evaluation.MeasureCollection
addInstanceInfo(Instance) - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Adds one instance to KDTree loosly.
addInstanceInfo(Instance) - Method in class moa.classifiers.lazy.neighboursearch.LinearNNSearch: Adds the given instance info.
addInstanceInfo(Instance) - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch: Adds information from the given instance without modifying the datastructure a lot.
addInstanceToTree(Instance, KDTreeNode) - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Recursively adds an instance to the tree starting from the supplied KDTreeNode.
addItem(int, List<Integer>, List<Double>) - Method in class moa.recommender.rc.data.AbstractRecommenderData
addItem(int, List<Integer>, List<Double>) - Method in class moa.recommender.rc.data.impl.MemRecommenderData
addItem(int, List<Integer>, List<Double>) - Method in interface moa.recommender.rc.data.RecommenderData
additionalPlotOption - Variable in class moa.tasks.Plot: Additional plot options.
additionalSetOption - Variable in class moa.tasks.Plot: Addition pre-plot gunplot commands.
addLearningAttempt(int, double[], double) - Method in class moa.evaluation.BasicClusteringPerformanceEvaluator
addLearningAttempt(int, double[], double) - Method in interface moa.evaluation.LearningPerformanceEvaluator
addMeasurementName(String) - Method in class moa.evaluation.LearningCurve
AddNode(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.MCOD.MicroCluster
AddNoiseFilter - Class in moa.streams.filters: Filter for adding random noise to examples in a stream.
AddNoiseFilter() - Constructor for class moa.streams.filters.AddNoiseFilter
addNoiseOption - Variable in class moa.streams.generators.WaveformGenerator
addObject(DataObject) - Method in class moa.clusterers.outliers.AnyOut.util.DataSet: Adds a DataObject to the set.
addObject(DataSet) - Method in class moa.clusterers.outliers.AnyOut.util.DataSet: Adds all objects in the given data set
addObservation(double, double) - Method in class moa.core.GaussianEstimator
addObservations(GaussianEstimator) - Method in class moa.core.GaussianEstimator
addOldLabel(double) - Method in class moa.classifiers.meta.TemporallyAugmentedClassifier
addOption(Option) - Method in class moa.options.Options
AddOutlier(MyBaseOutlierDetector.Outlier) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
AddPrecNeigh(Long) - Method in class moa.clusterers.outliers.Angiulli.ExactSTORM.ISBNodeExact
AddPrecNeigh(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
AddPrecNeigh(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBNode
addResult(Instance, double[]) - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator
addResult(Instance, double[]) - Method in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
addResult(Instance, double[]) - Method in class moa.evaluation.BasicRegressionPerformanceEvaluator
addResult(Instance, double[]) - Method in interface moa.evaluation.ClassificationPerformanceEvaluator: Adds a learning result to this evaluator.
addResult(Instance, double[]) - Method in class moa.evaluation.EWMAClassificationPerformanceEvaluator
addResult(Instance, double[]) - Method in class moa.evaluation.FadingFactorClassificationPerformanceEvaluator
addResult(Instance, double[]) - Method in class moa.evaluation.MultilabelWindowClassificationPerformanceEvaluator: Add a Result.
addResult(Instance, double[]) - Method in class moa.evaluation.WindowClassificationPerformanceEvaluator
addResult(Instance, double[]) - Method in class moa.evaluation.WindowRegressionPerformanceEvaluator
addTaskCompletionListener(TaskCompletionListener) - Method in class moa.tasks.TaskThread
addText(String) - Method in class moa.gui.TextViewerPanel
addTimePerObject(double) - Method in class moa.evaluation.OutlierPerformance
addToStored(Classifier, double) - Method in class moa.classifiers.meta.AccuracyUpdatedEnsemble: Adds a classifier to the storage.
addToStored(Classifier, double) - Method in class moa.classifiers.meta.AccuracyWeightedEnsemble: Adds a classifier to the storage.
addToStored(OnlineAccuracyUpdatedEnsemble.ClassifierWithMemory, double) - Method in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble: Adds a classifier to the storage.
addToValue(int, double) - Method in class moa.core.DoubleVector
addToValues(double) - Method in class moa.core.DoubleVector
addUser(int, List<Integer>, List<Double>) - Method in class moa.recommender.rc.data.AbstractRecommenderData
addUser(int, List<Integer>, List<Double>) - Method in class moa.recommender.rc.data.impl.MemRecommenderData
addUser(int, List<Integer>, List<Double>) - Method in interface moa.recommender.rc.data.RecommenderData
addValue(int, double) - Method in class moa.evaluation.MeasureCollection
addValue(String, double) - Method in class moa.evaluation.MeasureCollection
addValues(DoubleVector) - Method in class moa.core.DoubleVector
addValues(double[]) - Method in class moa.core.DoubleVector
addVectors(double[], double[]) - Static method in class moa.cluster.CFCluster: Adds the second array to the first array element by element.
addVote(double[], double) - Method in class moa.classifiers.rules.core.voting.AbstractErrorWeightedVote
addVote(double[], double) - Method in interface moa.classifiers.rules.core.voting.ErrorWeightedVote: Adds a vote and the corresponding error for the computation of the weighted vote and respective weighted error.
ADError - Variable in class moa.classifiers.meta.LeveragingBag
ADError - Variable in class moa.classifiers.meta.LimAttClassifier
ADError - Variable in class moa.classifiers.meta.OzaBagAdwin
ADError - Variable in class moa.classifiers.meta.OzaBoostAdwin
ADWIN - Class in moa.classifiers.core.driftdetection: ADaptive sliding WINdow method.
ADWIN() - Constructor for class moa.classifiers.core.driftdetection.ADWIN
ADWIN(double) - Constructor for class moa.classifiers.core.driftdetection.ADWIN
ADWIN(int) - Constructor for class moa.classifiers.core.driftdetection.ADWIN
adwin - Variable in class moa.classifiers.core.driftdetection.ADWINChangeDetector
ADWINChangeDetector - Class in moa.classifiers.core.driftdetection: Drift detection method based in ADWIN.
ADWINChangeDetector() - Constructor for class moa.classifiers.core.driftdetection.ADWINChangeDetector
adwinReplaceWorstClassifierOption - Variable in class moa.classifiers.meta.LimAttClassifier
afterAddInstance(KDTreeNode) - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Corrects the start and end indices of a KDTreeNode after an instance is added to the tree.
aggregate(ClusKernel, long, double) - Method in class moa.clusterers.clustree.ClusKernel: Make this cluster older bei weighting it and add to this cluster the given cluster.
aggregateCluster(ClusKernel, long, double) - Method in class moa.clusterers.clustree.Entry: Aggregate the given Kernel to the data cluster of this entry.
aggregateEntry(Entry, long, double) - Method in class moa.clusterers.clustree.Entry: Aggregate the data in the Kernel of the other Entry.
aggregateToBuffer(ClusKernel, long, double) - Method in class moa.clusterers.clustree.Entry: Aggregate the given Kernel to the buffer cluster of this entry.
AgrawalGenerator - Class in moa.streams.generators: Stream generator for Agrawal dataset.
AgrawalGenerator() - Constructor for class moa.streams.generators.AgrawalGenerator
AgrawalGenerator.ClassFunction - Interface in moa.streams.generators
alpha - Variable in class moa.classifiers.meta.OCBoost
alpha - Variable in class moa.classifiers.meta.OnlineSmoothBoost
alpha - Variable in class moa.classifiers.meta.OzaBagASHT
alpha - Variable in class moa.classifiers.rules.core.Rule.Builder
alpha(double) - Method in class moa.classifiers.rules.core.Rule.Builder
alpha - Variable in class moa.classifiers.rules.driftdetection.PageHinkleyTest
alpha - Variable in class moa.classifiers.trees.AdaHoeffdingOptionTree.AdaLearningNode
alpha - Variable in class moa.evaluation.EWMAClassificationPerformanceEvaluator.Estimator
alpha - Variable in class moa.evaluation.FadingFactorClassificationPerformanceEvaluator.Estimator
alphainc - Variable in class moa.classifiers.meta.OCBoost
alphaOption - Variable in class moa.classifiers.core.driftdetection.GeometricMovingAverageDM
alphaOption - Variable in class moa.classifiers.core.driftdetection.PageHinkleyDM
alphaOption - Variable in class moa.evaluation.EWMAClassificationPerformanceEvaluator
alphaOption - Variable in class moa.evaluation.FadingFactorClassificationPerformanceEvaluator
alphaOption - Variable in class moa.streams.ConceptDriftRealStream
alphaOption - Variable in class moa.streams.ConceptDriftStream
alphaOption - Variable in class moa.tasks.EvaluatePrequential
alphaOption - Variable in class moa.tasks.EvaluatePrequentialRegression
Alternate - Variable in class moa.classifiers.trees.ORTO.Node
alternateTree - Variable in class moa.classifiers.trees.FIMTDD.Node
alternateTree - Variable in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaSplitNode
alternateTree - Variable in class moa.classifiers.trees.ORTO.Node
alternateTreeFadingFactorOption - Variable in class moa.classifiers.trees.FIMTDD
AlternateTreeFadingFactorOption - Variable in class moa.classifiers.trees.ORTO
alternateTrees - Variable in class moa.classifiers.trees.HoeffdingAdaptiveTree
alternateTreeTimeOption - Variable in class moa.classifiers.trees.FIMTDD
AlternateTreeTimeOption - Variable in class moa.classifiers.trees.ORTO
alternateTreeTMinOption - Variable in class moa.classifiers.trees.FIMTDD
AlternateTreeTMinOption - Variable in class moa.classifiers.trees.ORTO
amRules - Variable in class moa.classifiers.rules.core.Rule
amRules - Variable in class moa.classifiers.rules.core.Rule.Builder
amRules(AbstractAMRules) - Method in class moa.classifiers.rules.core.Rule.Builder
amRules - Variable in class moa.classifiers.rules.core.RuleActiveLearningNode
AMRulesRegressor - Class in moa.classifiers.rules
AMRulesRegressor() - Constructor for class moa.classifiers.rules.AMRulesRegressor
anomalyDetectionOption - Variable in class moa.classifiers.rules.RuleClassifier
anomalyNumInstThresholdOption - Variable in class moa.classifiers.rules.AbstractAMRules
anomalyNumInstThresholdOption - Variable in class moa.classifiers.rules.RuleClassifier
anomalyProbabilityThresholdOption - Variable in class moa.classifiers.rules.RuleClassifier
AnyOut - Class in moa.clusterers.outliers.AnyOut
AnyOut() - Constructor for class moa.clusterers.outliers.AnyOut.AnyOut
AnyOutCore - Class in moa.clusterers.outliers.AnyOut
AnyOutCore() - Constructor for class moa.clusterers.outliers.AnyOut.AnyOutCore
appendIndent(StringBuilder, int) - Static method in class moa.core.StringUtils
appendIndented(StringBuilder, int, String) - Static method in class moa.core.StringUtils
appendNewline(StringBuilder) - Static method in class moa.core.StringUtils
appendNewlineIndented(StringBuilder, int, String) - Static method in class moa.core.StringUtils
applyChanges() - Method in class moa.gui.clustertab.ClusteringAlgoPanel
applyChanges() - Method in class moa.gui.OptionsConfigurationPanel
applyChanges() - Method in class moa.gui.outliertab.OutlierAlgoPanel
applyDrawDecay(float, boolean) - Method in class moa.gui.visualization.StreamOutlierPanel
applyDrawDecay(float) - Method in class moa.gui.visualization.StreamPanel
applyState() - Method in class moa.gui.ClassOptionEditComponent
applyState() - Method in class moa.gui.ClassOptionWithNamesEditComponent
applyState() - Method in class moa.gui.FileOptionEditComponent
applyState() - Method in class moa.gui.FlagOptionEditComponent
applyState() - Method in class moa.gui.FloatOptionEditComponent
applyState() - Method in class moa.gui.IntOptionEditComponent
applyState() - Method in class moa.gui.MultiChoiceOptionEditComponent
applyState() - Method in interface moa.gui.OptionEditComponent: This method applies the state
applyState() - Method in class moa.gui.StringOptionEditComponent
applyState() - Method in class moa.gui.WEKAClassOptionEditComponent
ApplyToCanvas(BufferedImage) - Method in class moa.gui.visualization.StreamOutlierPanel
ApproxSTORM - Class in moa.clusterers.outliers.Angiulli
ApproxSTORM() - Constructor for class moa.clusterers.outliers.Angiulli.ApproxSTORM
ApproxSTORM.ISBNodeAppr - Class in moa.clusterers.outliers.Angiulli
ApproxSTORM.ISBNodeAppr(Instance, StreamObj, Long, int) - Constructor for class moa.clusterers.outliers.Angiulli.ApproxSTORM.ISBNodeAppr
arffFileOption - Variable in class moa.streams.ArffFileStream
arffFileOption - Variable in class moa.streams.clustering.FileStream
arffFileOption - Variable in class moa.tasks.WriteStreamToARFFFile
ArffFileStream - Class in moa.streams: Stream reader of ARFF files.
ArffFileStream() - Constructor for class moa.streams.ArffFileStream
ArffFileStream(String, int) - Constructor for class moa.streams.ArffFileStream
array - Variable in class moa.core.DoubleVector
ASHoeffdingTree - Class in moa.classifiers.trees: Adaptive Size Hoeffding Tree used in Bagging using trees of different size.
ASHoeffdingTree() - Constructor for class moa.classifiers.trees.ASHoeffdingTree
assignSubToCenters(KDTreeNode, Instances, int[], int[]) - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Assigns instances of this node to center.
attachUpdatable(Updatable) - Method in class moa.recommender.rc.data.AbstractRecommenderData
attachUpdatable(Updatable) - Method in interface moa.recommender.rc.data.RecommenderData
attemptToSplit(HoeffdingTree.ActiveLearningNode, HoeffdingTree.SplitNode, int) - Method in class moa.classifiers.multilabel.HoeffdingTreeClassifLeaves
attemptToSplit(FIMTDD.LeafNode, FIMTDD.SplitNode, int) - Method in class moa.classifiers.trees.FIMTDD
attemptToSplit(HoeffdingOptionTree.ActiveLearningNode, HoeffdingOptionTree.SplitNode, int) - Method in class moa.classifiers.trees.HoeffdingOptionTree
attemptToSplit(HoeffdingTree.ActiveLearningNode, HoeffdingTree.SplitNode, int) - Method in class moa.classifiers.trees.HoeffdingTree
attIndex - Variable in class moa.classifiers.core.conditionaltests.NominalAttributeBinaryTest
attIndex - Variable in class moa.classifiers.core.conditionaltests.NominalAttributeMultiwayTest
attIndex - Variable in class moa.classifiers.core.conditionaltests.NumericAttributeBinaryTest
attIndex - Variable in class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
attNoiseFractionOption - Variable in class moa.streams.filters.AddNoiseFilter
AttributeClassObserver - Interface in moa.classifiers.core.attributeclassobservers: Interface for observing the class data distribution for an attribute.
attributeIndicesTipText() - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Returns the tip text for this property.
attributeMissingValues - Variable in class moa.classifiers.rules.RuleClassification
attributeObservers - Variable in class moa.classifiers.bayes.NaiveBayes
attributeObservers - Variable in class moa.classifiers.rules.RuleClassifier
attributeObservers - Variable in class moa.classifiers.trees.DecisionStump
attributeObservers - Variable in class moa.classifiers.trees.FIMTDD.Node
attributeObservers - Variable in class moa.classifiers.trees.HoeffdingOptionTree.ActiveLearningNode
attributeObservers - Variable in class moa.classifiers.trees.HoeffdingTree.ActiveLearningNode
attributeObservers - Variable in class moa.classifiers.trees.ORTO.ActiveLearningNode
attributeObserversGauss - Variable in class moa.classifiers.rules.RuleClassifier
AttributeSplitSuggestion - Class in moa.classifiers.core: Class for computing attribute split suggestions given a split test.
AttributeSplitSuggestion(InstanceConditionalTest, double[][], double) - Constructor for class moa.classifiers.core.AttributeSplitSuggestion
attributesProbability - Variable in class moa.classifiers.rules.RuleClassification
attributeStatistics - Variable in class moa.classifiers.rules.RuleClassification
attributeStatistics - Variable in class moa.classifiers.trees.ORTO.ORTOPerceptron
attributeStatisticsSupervised - Variable in class moa.classifiers.rules.RuleClassification
attValDistPerClass - Variable in class moa.classifiers.core.attributeclassobservers.GaussianNumericAttributeClassObserver
attValDistPerClass - Variable in class moa.classifiers.core.attributeclassobservers.GreenwaldKhannaNumericAttributeClassObserver
attValDistPerClass - Variable in class moa.classifiers.core.attributeclassobservers.NominalAttributeClassObserver
attValObservers - Variable in class moa.streams.filters.AddNoiseFilter
attValue - Variable in class moa.classifiers.core.conditionaltests.NominalAttributeBinaryTest
attValue - Variable in class moa.classifiers.core.conditionaltests.NumericAttributeBinaryTest
attValue - Variable in class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
AutoClassDiscovery - Class in moa.core: Class for discovering classes via reflection in the java class path.
AutoClassDiscovery() - Constructor for class moa.core.AutoClassDiscovery
AutoExpandVector<T> - Class in moa.core: Vector with the capability of automatic expansion.
AutoExpandVector() - Constructor for class moa.core.AutoExpandVector
AutoExpandVector(int) - Constructor for class moa.core.AutoExpandVector
autoFreqStrings - Static variable in class moa.gui.PreviewPanel
autoFreqTimeSecs - Static variable in class moa.gui.PreviewPanel
autoRefreshComboBox - Variable in class moa.gui.PreviewPanel
autoRefreshLabel - Variable in class moa.gui.PreviewPanel
autoRefreshTimer - Variable in class moa.gui.PreviewPanel
averageError - Variable in class moa.evaluation.BasicRegressionPerformanceEvaluator
averageError - Variable in class moa.evaluation.WindowRegressionPerformanceEvaluator
averageMeasurements(Measurement[][]) - Static method in class moa.core.Measurement
averageTargetError - Variable in class moa.evaluation.BasicRegressionPerformanceEvaluator
AWTInteractiveRenderer - Interface in moa.gui
AWTRenderable - Interface in moa.gui: Interface representing a component that is renderable
AWTRenderer - Interface in moa.gui: Interface representing a component to edit an option.

B

b - Variable in class moa.evaluation.FadingFactorClassificationPerformanceEvaluator.Estimator
balanceClassesOption - Variable in class moa.streams.generators.AgrawalGenerator
balanceClassesOption - Variable in class moa.streams.generators.SEAGenerator
balanceClassesOption - Variable in class moa.streams.generators.STAGGERGenerator
baseLearner - Variable in class moa.classifiers.meta.TemporallyAugmentedClassifier
baseLearnerOption - Variable in class moa.classifiers.active.ActiveClassifier
baseLearnerOption - Variable in class moa.classifiers.drift.DriftDetectionMethodClassifier
baseLearnerOption - Variable in class moa.classifiers.meta.LeveragingBag
baseLearnerOption - Variable in class moa.classifiers.meta.LimAttClassifier
baseLearnerOption - Variable in class moa.classifiers.meta.OCBoost
baseLearnerOption - Variable in class moa.classifiers.meta.OnlineSmoothBoost
baseLearnerOption - Variable in class moa.classifiers.meta.OzaBag
baseLearnerOption - Variable in class moa.classifiers.meta.OzaBagAdwin
baseLearnerOption - Variable in class moa.classifiers.meta.OzaBoost
baseLearnerOption - Variable in class moa.classifiers.meta.OzaBoostAdwin
baseLearnerOption - Variable in class moa.classifiers.meta.RandomRules
baseLearnerOption - Variable in class moa.classifiers.meta.TemporallyAugmentedClassifier
baseLearnerOption - Variable in class moa.classifiers.meta.WEKAClassifier
BaselinePredictor - Class in moa.recommender.predictor: A naive algorithm which combines the global mean of all the existing ratings, the mean rating of the user and the mean rating of the item to make a prediction.
BaselinePredictor() - Constructor for class moa.recommender.predictor.BaselinePredictor
BaselinePredictor - Class in moa.recommender.rc.predictor.impl
BaselinePredictor(RecommenderData) - Constructor for class moa.recommender.rc.predictor.impl.BaselinePredictor
BasicClassificationPerformanceEvaluator - Class in moa.evaluation: Classification evaluator that performs basic incremental evaluation.
BasicClassificationPerformanceEvaluator() - Constructor for class moa.evaluation.BasicClassificationPerformanceEvaluator
BasicClusteringPerformanceEvaluator - Class in moa.evaluation: Clustering evaluator that performs basic incremental evaluation.
BasicClusteringPerformanceEvaluator() - Constructor for class moa.evaluation.BasicClusteringPerformanceEvaluator
BasicConceptDriftPerformanceEvaluator - Class in moa.evaluation
BasicConceptDriftPerformanceEvaluator() - Constructor for class moa.evaluation.BasicConceptDriftPerformanceEvaluator
BasicRegressionPerformanceEvaluator - Class in moa.evaluation: Regression evaluator that performs basic incremental evaluation.
BasicRegressionPerformanceEvaluator() - Constructor for class moa.evaluation.BasicRegressionPerformanceEvaluator
BatchCmd - Class in moa.gui
BatchCmd(AbstractClusterer, ClusteringStream, MeasureCollection[], int) - Constructor for class moa.gui.BatchCmd
bestSplit - Variable in class moa.classifiers.trees.DecisionStump
bestSuggestion - Variable in class moa.classifiers.rules.core.RuleActiveLearningNode
betaOption - Variable in class moa.classifiers.meta.WeightedMajorityAlgorithm
betaOption - Variable in class moa.clusterers.denstream.WithDBSCAN
bigTreesOption - Variable in class moa.classifiers.meta.LimAttClassifier
binaryGeneratorOption - Variable in class moa.streams.generators.multilabel.MetaMultilabelGenerator
binarySplitsOption - Variable in class moa.classifiers.trees.DecisionStump
binarySplitsOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree
binarySplitsOption - Variable in class moa.classifiers.trees.HoeffdingTree
BinaryTreeNumericAttributeClassObserver - Class in moa.classifiers.core.attributeclassobservers: Class for observing the class data distribution for a numeric attribute using a binary tree.
BinaryTreeNumericAttributeClassObserver() - Constructor for class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserver
BinaryTreeNumericAttributeClassObserver.Node - Class in moa.classifiers.core.attributeclassobservers
BinaryTreeNumericAttributeClassObserver.Node(double, int, double) - Constructor for class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserver.Node
BinaryTreeNumericAttributeClassObserverRegression - Class in moa.classifiers.core.attributeclassobservers: Class for observing the class data distribution for a numeric attribute using a binary tree.
BinaryTreeNumericAttributeClassObserverRegression() - Constructor for class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserverRegression
BinaryTreeNumericAttributeClassObserverRegression.Node - Class in moa.classifiers.core.attributeclassobservers
BinaryTreeNumericAttributeClassObserverRegression.Node(double, double) - Constructor for class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserverRegression.Node
binList - Variable in class moa.classifiers.core.attributeclassobservers.VFMLNumericAttributeClassObserver
blockSeqDrift2Option - Variable in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector
blockSeqDriftOption - Variable in class moa.classifiers.core.driftdetection.SeqDrift1ChangeDetector
boundaryClass - Variable in class moa.classifiers.core.attributeclassobservers.VFMLNumericAttributeClassObserver.Bin
boundaryWeight - Variable in class moa.classifiers.core.attributeclassobservers.VFMLNumericAttributeClassObserver.Bin
bOutlier - Variable in class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBNode
branchForInstance(Instance) - Method in class moa.classifiers.core.conditionaltests.InstanceConditionalTest: Returns the number of the branch for an instance, -1 if unknown.
branchForInstance(Instance) - Method in class moa.classifiers.core.conditionaltests.NominalAttributeBinaryTest
branchForInstance(Instance) - Method in class moa.classifiers.core.conditionaltests.NominalAttributeMultiwayTest
branchForInstance(Instance) - Method in class moa.classifiers.core.conditionaltests.NumericAttributeBinaryTest
branchForInstance(Instance) - Method in class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
breadthFirstStrat - Variable in class moa.clusterers.clustree.ClusTree: Parameter to determine wich strategy to use
BRISMFPredictor - Class in moa.recommender.predictor: Implementation of the algorithm described in Scalable Collaborative Filtering Approaches for Large Recommender Systems (Gábor Takács, István Pilászy, Bottyán Németh, and Domonkos Tikk).
BRISMFPredictor() - Constructor for class moa.recommender.predictor.BRISMFPredictor
BRISMFPredictor - Class in moa.recommender.rc.predictor.impl: Implementation of the algorithm described in Scalable Collaborative Filtering Approaches for Large Recommender Systems (Gábor Takács, István Pilászy, Bottyán Németh, and Domonkos Tikk).
BRISMFPredictor(int, RecommenderData, boolean) - Constructor for class moa.recommender.rc.predictor.impl.BRISMFPredictor
BRISMFPredictor(int, RecommenderData, double, double, boolean) - Constructor for class moa.recommender.rc.predictor.impl.BRISMFPredictor
browseButton - Variable in class moa.gui.FileOptionEditComponent
browseForFile() - Method in class moa.gui.FileOptionEditComponent
bShowProgress - Variable in class moa.clusterers.outliers.MyBaseOutlierDetector
bStopAlgorithm - Variable in class moa.clusterers.outliers.MyBaseOutlierDetector
bTrace - Variable in class moa.clusterers.outliers.MyBaseOutlierDetector
BucketManager - Class in moa.clusterers.streamkm
BucketManager(int, int, int, MTRandom) - Constructor for class moa.clusterers.streamkm.BucketManager: initializes a bucketmanager for n points with bucketsize maxsize and dimension d
BucketManager.Bucket - Class in moa.clusterers.streamkm
BucketManager.Bucket(int, int) - Constructor for class moa.clusterers.streamkm.BucketManager.Bucket
buckets - Variable in class moa.clusterers.streamkm.BucketManager
Budget - Interface in moa.clusterers.clustree.util: This is an interface for classes that are to be given along with every data point inserted in the tree.
budgetOption - Variable in class moa.classifiers.active.ActiveClassifier
build() - Method in class moa.classifiers.rules.core.Rule.Builder
build() - Method in class moa.cluster.Miniball: Recalculate Miniball parameter Center and Radius
buildClassifier() - Method in class moa.classifiers.meta.WEKAClassifier
buildClassifier(Instances) - Method in class weka.classifiers.meta.MOA: Generates a classifier.
buildingModelTree() - Method in class moa.classifiers.trees.FIMTDD
buildKDTree(Instances) - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Builds the KDTree on the supplied set of instances/points.
buildTree(DataSet) - Method in class moa.clusterers.outliers.AnyOut.util.EMTopDownTreeBuilder
bWarning - Variable in class moa.clusterers.outliers.AbstractC.AbstractCBase
bWarning - Variable in class moa.clusterers.outliers.MCOD.MCODBase
bWarning - Variable in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
byteSizeEstimateOverheadFraction - Variable in class moa.classifiers.trees.HoeffdingOptionTree
byteSizeEstimateOverheadFraction - Variable in class moa.classifiers.trees.HoeffdingTree
byteSizeEstimateOverheadFraction - Variable in class moa.classifiers.trees.ORTO

C

c_max - Variable in class moa.classifiers.core.driftdetection.HDDM_A_Test
c_min - Variable in class moa.classifiers.core.driftdetection.HDDM_A_Test
cache - Variable in class moa.streams.filters.CacheFilter
cached(DistanceFunction<Data>) - Static method in class moa.clusterers.outliers.utils.mtree.DistanceFunctions: Creates a cached version of a distance function.
cachedClassNames - Static variable in class moa.core.AutoClassDiscovery
CachedInstancesStream - Class in moa.streams: Stream generator for representing a stream that is cached in memory.
CachedInstancesStream(Instances) - Constructor for class moa.streams.CachedInstancesStream
CacheFilter - Class in moa.streams.filters: Filter for representing a stream that is cached in memory.
CacheFilter() - Constructor for class moa.streams.filters.CacheFilter
CacheShuffledStream - Class in moa.tasks: Task for storing and shuffling examples in memory.
CacheShuffledStream() - Constructor for class moa.tasks.CacheShuffledStream
cacheTestOption - Variable in class moa.tasks.EvaluatePeriodicHeldOutTest
calcByteSize() - Method in class moa.classifiers.trees.FIMTDD
calcByteSize() - Method in class moa.classifiers.trees.FIMTDD.Node
calcByteSize() - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaLearningNode
calcByteSize() - Method in class moa.classifiers.trees.HoeffdingOptionTree.ActiveLearningNode
calcByteSize() - Method in class moa.classifiers.trees.HoeffdingOptionTree
calcByteSize() - Method in class moa.classifiers.trees.HoeffdingOptionTree.Node
calcByteSize() - Method in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
calcByteSize() - Method in class moa.classifiers.trees.HoeffdingTree.ActiveLearningNode
calcByteSize() - Method in class moa.classifiers.trees.HoeffdingTree
calcByteSize() - Method in class moa.classifiers.trees.HoeffdingTree.Node
calcByteSize() - Method in class moa.classifiers.trees.HoeffdingTree.SplitNode
calcByteSize() - Method in class moa.classifiers.trees.ORTO.ActiveLearningNode
calcByteSize() - Method in class moa.classifiers.trees.ORTO
calcByteSize() - Method in class moa.classifiers.trees.ORTO.InnerNode
calcByteSize() - Method in class moa.classifiers.trees.ORTO.Node
calcByteSizeIncludingSubtree() - Method in class moa.classifiers.trees.FIMTDD.Node
calcByteSizeIncludingSubtree() - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaSplitNode
calcByteSizeIncludingSubtree() - Method in class moa.classifiers.trees.HoeffdingOptionTree.Node
calcByteSizeIncludingSubtree() - Method in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
calcByteSizeIncludingSubtree() - Method in class moa.classifiers.trees.HoeffdingTree.Node
calcByteSizeIncludingSubtree() - Method in class moa.classifiers.trees.HoeffdingTree.SplitNode
calcDistance(ClusKernel) - Method in class moa.clusterers.clustree.ClusKernel: Calculate the distance to this other cluster.
calcDistance(ClusKernel) - Method in class moa.clusterers.clustree.Entry: Calculates the distance to the data in this entry.
calcDistance(Entry) - Method in class moa.clusterers.clustree.Entry: Calculates the distance to the data in this entry of the data in the given entry.
calcLogLoss(double, double, double) - Static method in class moa.core.utils.EvalUtils: Calculate Log Loss.
calculate(DATA, DATA) - Method in interface moa.clusterers.outliers.utils.mtree.DistanceFunction
calculateDetph(ORTO) - Method in class moa.classifiers.trees.ORTO.InnerNode
calculateDetph(ORTO) - Method in class moa.classifiers.trees.ORTO.Node
calculatePromise() - Method in class moa.classifiers.trees.HoeffdingOptionTree.Node
calculatePromise() - Method in class moa.classifiers.trees.HoeffdingTree.Node
calibrateThreshold(ArrayList<double[]>, double) - Static method in class moa.core.utils.EvalUtils: Calibrate a threshold.
calibrateThresholds(ArrayList<double[]>, double[]) - Static method in class moa.core.utils.EvalUtils: Calibrate thresholds.
cancelFlag - Variable in class moa.tasks.StandardTaskMonitor
cancelSelectedTasks() - Method in class moa.gui.conceptdrift.CDTaskManagerPanel
cancelSelectedTasks() - Method in class moa.gui.RegressionTaskManagerPanel
cancelSelectedTasks() - Method in class moa.gui.TaskManagerPanel
cancelTask() - Method in class moa.tasks.TaskThread
cancelTaskButton - Variable in class moa.gui.conceptdrift.CDTaskManagerPanel
cancelTaskButton - Variable in class moa.gui.RegressionTaskManagerPanel
cancelTaskButton - Variable in class moa.gui.TaskManagerPanel
candidate - Variable in class moa.classifiers.meta.AccuracyUpdatedEnsemble: Candidate classifier.
candidate - Variable in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble: Candidate classifier.
candidateClassifier - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble
candidateIsFullOwner(KDTreeNode, Instance, Instance) - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Returns true if candidate is a full owner in respect to a competitor.
caseAnomaly - Variable in class moa.classifiers.rules.RuleClassifier
caseAnomalySupervised - Variable in class moa.classifiers.rules.RuleClassifier
cds - Variable in class moa.classifiers.core.driftdetection.EnsembleDriftDetectionMethods
CDTaskManagerPanel - Class in moa.gui.conceptdrift: This panel displays the running tasks.
CDTaskManagerPanel() - Constructor for class moa.gui.conceptdrift.CDTaskManagerPanel
CDTaskManagerPanel.ProgressCellRenderer - Class in moa.gui.conceptdrift
CDTaskManagerPanel.ProgressCellRenderer() - Constructor for class moa.gui.conceptdrift.CDTaskManagerPanel.ProgressCellRenderer
CDTaskManagerPanel.TaskTableModel - Class in moa.gui.conceptdrift
CDTaskManagerPanel.TaskTableModel() - Constructor for class moa.gui.conceptdrift.CDTaskManagerPanel.TaskTableModel
center() - Method in class moa.cluster.Miniball: Return the center of the Miniball
centerInstances(Instances, int[], double) - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Assigns instances to centers using KDTree.
centre - Variable in class moa.streams.generators.RandomRBFGenerator.Centroid
centresStreamingCoreset - Variable in class moa.clusterers.streamkm.StreamKM
centroids - Variable in class moa.streams.generators.RandomRBFGenerator
centroidWeights - Variable in class moa.streams.generators.RandomRBFGenerator
cEstimacion - Variable in class moa.classifiers.core.driftdetection.HDDM_A_Test
CFCluster - Class in moa.cluster
CFCluster(Instance, int) - Constructor for class moa.cluster.CFCluster: Instantiates an empty kernel with the given dimensionality.
CFCluster(int) - Constructor for class moa.cluster.CFCluster
CFCluster(double[], int) - Constructor for class moa.cluster.CFCluster
CFCluster(CFCluster) - Constructor for class moa.cluster.CFCluster
change - Variable in class moa.streams.generators.cd.AbstractConceptDriftGenerator
changeCluster(ClusterEvent) - Method in class moa.gui.BatchCmd
changeCluster(ClusterEvent) - Method in class moa.gui.visualization.RunOutlierVisualizer
changeCluster(ClusterEvent) - Method in class moa.gui.visualization.RunVisualizer
changeCluster(ClusterEvent) - Method in interface moa.streams.clustering.ClusterEventListener
changeDetected - Variable in class moa.classifiers.drift.DriftDetectionMethodClassifier
changeDetection - Variable in class moa.classifiers.rules.core.Rule.Builder
changeDetection(boolean) - Method in class moa.classifiers.rules.core.Rule.Builder
changeDetection - Variable in class moa.classifiers.rules.core.RuleActiveLearningNode
changeDetection - Variable in class moa.classifiers.trees.FIMTDD.Node
ChangeDetectionMeasures - Class in moa.evaluation
ChangeDetectionMeasures() - Constructor for class moa.evaluation.ChangeDetectionMeasures
ChangeDetector - Interface in moa.classifiers.core.driftdetection: Change Detector interface to implement methods that detects change.
ChangeDetectorLearner - Class in moa.learners: Class for detecting concept drift and to be used as a learner.
ChangeDetectorLearner() - Constructor for class moa.learners.ChangeDetectorLearner
changeDetectorsOption - Variable in class moa.classifiers.core.driftdetection.EnsembleDriftDetectionMethods
changeDriftOption - Variable in class moa.streams.generators.cd.GradualChangeGenerator
changeListeners - Variable in class moa.gui.ClassOptionEditComponent: listeners that listen to changes to the chosen option.
changeListeners - Variable in class moa.gui.ClassOptionWithNamesEditComponent: listeners that listen to changes to the chosen option.
check_in(double[]) - Method in class moa.cluster.Miniball: Adds a point to the list.
Skip action on null parameter.
checkBestAttrib(double, AutoExpandVector<AttributeClassObserver>, DoubleVector) - Method in class moa.classifiers.rules.RuleClassifier
checkForSplit(FIMTDD) - Method in class moa.classifiers.trees.FIMTDD.LeafNode
checkMissing(Instances) - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Checks if there is any instance with missing values.
checkMissing(Instance) - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Checks if there is any missing value in the given instance.
checkRoot() - Method in class moa.classifiers.trees.FIMTDD
checkRoot() - Method in class moa.classifiers.trees.ORTO
children - Variable in class moa.classifiers.trees.FIMTDD.SplitNode
children - Variable in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
children - Variable in class moa.classifiers.trees.HoeffdingTree.SplitNode
children - Variable in class moa.classifiers.trees.ORTO.InnerNode
children - Variable in class moa.streams.generators.RandomTreeGenerator.Node
chooseRandomIndexBasedOnWeights(double[], Random) - Static method in class moa.core.MiscUtils
chosenObject - Variable in class moa.gui.ClassOptionSelectionPanel
chosenObject - Variable in class moa.gui.ClassOptionWithNamesSelectionPanel
chosenObjectEditor - Variable in class moa.gui.ClassOptionSelectionPanel
chosenObjectEditor - Variable in class moa.gui.ClassOptionWithNamesSelectionPanel
chosenOptionIndex - Variable in class moa.options.MultiChoiceOption
chunkSize - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble
chunkSizeOption - Variable in class moa.classifiers.meta.AccuracyUpdatedEnsemble: Chunk size.
chunkSizeOption - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble: Chunk size.
chunkSizeOption - Variable in class moa.tasks.EvaluateInterleavedChunks: Allow to define the training/testing chunk size.
cindex(Clustering, ArrayList<DataPoint>) - Method in class moa.evaluation.StatisticalCollection
classAccuracy - Variable in class moa.evaluation.WindowClassificationPerformanceEvaluator
classChoiceBox - Variable in class moa.gui.ClassOptionSelectionPanel
classChoiceBox - Variable in class moa.gui.ClassOptionWithNamesSelectionPanel
classChoiceChanged(Object) - Method in class moa.gui.ClassOptionSelectionPanel
classChoiceChanged(Object) - Method in class moa.gui.ClassOptionWithNamesSelectionPanel
classCountsLeft - Variable in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserver.Node
classCountsRight - Variable in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserver.Node
classDistributions - Variable in class moa.classifiers.meta.AccuracyUpdatedEnsemble: Class distributions.
classDistributions - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble
classDistributions - Variable in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble: Class distributions.
classificationFunctions - Static variable in class moa.streams.generators.AgrawalGenerator
classificationFunctions - Static variable in class moa.streams.generators.SEAGenerator
classificationFunctions - Static variable in class moa.streams.generators.STAGGERGenerator
ClassificationMeasureCollection - Interface in moa.evaluation: Classification Measure Collection interface that it is used to not appear in clustering
ClassificationPerformanceEvaluator - Interface in moa.evaluation: Interface implemented by learner evaluators to monitor the results of the learning process.
ClassificationTabPanel - Class in moa.gui: This panel allows the user to select and configure a task, and run it.
ClassificationTabPanel() - Constructor for class moa.gui.ClassificationTabPanel
classifier - Variable in class moa.classifiers.active.ActiveClassifier
Classifier - Interface in moa.classifiers: Classifier interface for incremental classification models.
classifier - Variable in class moa.classifiers.drift.DriftDetectionMethodClassifier
classifier - Variable in class moa.classifiers.meta.WEKAClassifier
classifier - Variable in class moa.classifiers.multilabel.HoeffdingTreeClassifLeaves.LearningNodeClassifier
classifierParameterOption - Variable in class moa.tasks.RunTasks
classifierPurposeString - Static variable in class moa.clusterers.CobWeb
classifierRandom - Variable in class moa.classifiers.AbstractClassifier: Random Generator used in randomizable learners
classifierRandom - Variable in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaLearningNode
classifierRandom - Variable in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaSplitNode
classifierTipText() - Method in class weka.classifiers.meta.MOA: Returns the tooltip displayed in the GUI.
classifyInstance(RandomTreeGenerator.Node, double[]) - Method in class moa.streams.generators.RandomTreeGenerator
classIndexOption - Variable in class moa.streams.ArffFileStream
classIndexOption - Variable in class moa.streams.clustering.FileStream
classLabel - Variable in class moa.streams.generators.RandomRBFGenerator.Centroid
classLabel - Variable in class moa.streams.generators.RandomTreeGenerator.Node
classNoiseFractionOption - Variable in class moa.streams.filters.AddNoiseFilter
ClassOption - Class in moa.options: Class option.
ClassOption(String, char, String, Class<?>, String) - Constructor for class moa.options.ClassOption
ClassOption(String, char, String, Class<?>, String, String) - Constructor for class moa.options.ClassOption
ClassOptionEditComponent - Class in moa.gui: An OptionEditComponent that lets the user edit a class option.
ClassOptionEditComponent(ClassOption) - Constructor for class moa.gui.ClassOptionEditComponent
classOptionNamesToPreparedObjects - Variable in class moa.options.AbstractOptionHandler: Dictionary with option texts and objects
ClassOptionSelectionPanel - Class in moa.gui: Creates a panel that displays the classes available, letting the user select a class.
ClassOptionSelectionPanel(Class<?>, String, String) - Constructor for class moa.gui.ClassOptionSelectionPanel
ClassOptionWithNames - Class in moa.options
ClassOptionWithNames(String, char, String, Class<?>, String, String[]) - Constructor for class moa.options.ClassOptionWithNames
ClassOptionWithNames(String, char, String, Class<?>, String, String, String[]) - Constructor for class moa.options.ClassOptionWithNames
ClassOptionWithNamesEditComponent - Class in moa.gui
ClassOptionWithNamesEditComponent(ClassOptionWithNames) - Constructor for class moa.gui.ClassOptionWithNamesEditComponent
ClassOptionWithNamesSelectionPanel - Class in moa.gui
ClassOptionWithNamesSelectionPanel(Class<?>, String, String, String[]) - Constructor for class moa.gui.ClassOptionWithNamesSelectionPanel
classToCLIString(Class<?>, Class<?>) - Static method in class moa.options.AbstractClassOption: Gets the command line interface text of the class.
classValues(List<? extends Instance>) - Static method in class moa.cluster.Clustering
classWeights - Variable in class moa.classifiers.core.attributeclassobservers.VFMLNumericAttributeClassObserver.Bin
clean(int) - Method in class moa.evaluation.MeasureCollection
cleanUpKMeans(Clustering, ArrayList<CFCluster>) - Static method in class moa.clusterers.clustream.WithKmeans: Rearrange the k-means result into a set of CFClusters, cleaning up the redundancies.
clear() - Method in class moa.cluster.Miniball: Method clear: clears the ArrayList of the selection points.
Use it for starting a new selection list to calculate Bounding Sphere on
or to clear memory references to the list of objects.
Always use at the end of a Miniball use if you want to reuse later the Miniball object
clear() - Method in class moa.clusterers.clustree.ClusKernel: Remove all points from this cluster.
clear() - Method in class moa.clusterers.clustree.Entry: Clear the Entry.
clear() - Method in class moa.clusterers.clustree.Node: Clear this Node, which means that the noiseBuffer is cleared, that shallowClear is called upon all the entries of the node, that the split counter is set to zero and the node is set to not be a fake root.
clear() - Method in class moa.clusterers.outliers.AnyOut.util.DataSet
clear() - Method in class moa.core.AutoExpandVector
clear() - Method in class moa.recommender.rc.data.AbstractRecommenderData
clear() - Method in class moa.recommender.rc.data.impl.MemRecommenderData
clear() - Method in interface moa.recommender.rc.data.RecommenderData
clearEvents() - Method in class moa.gui.visualization.StreamOutlierPanel
clearPoints() - Method in class moa.gui.visualization.StreamOutlierPanel
cliChar - Variable in class moa.options.AbstractOption: Command line interface text of this option.
clipToInsideHrect(KDTreeNode, Instance) - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Finds the closest point in the hyper rectangle to a given point.
cliStringToDouble(String) - Static method in class moa.options.FloatOption
cliStringToInt(String) - Static method in class moa.options.IntOption
cliStringToObject(String, Class<?>, Option[]) - Static method in class moa.options.ClassOption
cliStringToObject(String, Class<?>, Option[]) - Static method in class moa.options.ClassOptionWithNames
cliStringToObject(String, Class<?>, Option[]) - Static method in class moa.options.WEKAClassOption
cliStringToOptionArray(String, char, Option) - Static method in class moa.options.ListOption
clone() - Method in class moa.clusterers.streamkm.Point
close() - Method in class moa.recommender.rc.data.AbstractRecommenderData
close() - Method in interface moa.recommender.rc.data.RecommenderData
closeDialog() - Method in class weka.gui.MOAClassOptionEditor: Closes the dialog.
closestPoint(Instance, Instances, int[]) - Method in class moa.classifiers.lazy.neighboursearch.EuclideanDistance: Returns the index of the closest point to the current instance.
ClusKernel - Class in moa.clusterers.clustree: Representation of an Entry in the tree
ClusKernel(double[], int) - Constructor for class moa.clusterers.clustree.ClusKernel: A constructor that makes a Kernel which just represents the given point.
ClusKernel(int) - Constructor for class moa.clusterers.clustree.ClusKernel: Constructor of the Cluster.
ClusKernel(ClusKernel) - Constructor for class moa.clusterers.clustree.ClusKernel: Instantiates a copy of the given cluster.
Cluster - Class in moa.cluster
Cluster() - Constructor for class moa.cluster.Cluster
clusterAddOption - Variable in class moa.clusterers.ClusterGenerator
Clusterer - Interface in moa.clusterers
clustererRandom - Variable in class moa.clusterers.AbstractClusterer
clustererRandom - Variable in class moa.clusterers.streamkm.BucketManager
clustererRandom - Variable in class moa.clusterers.streamkm.StreamKM
ClusterEvent - Class in moa.streams.clustering
ClusterEvent(Object, long, String, String) - Constructor for class moa.streams.clustering.ClusterEvent
ClusterEventListener - Interface in moa.streams.clustering
clusterEvents - Variable in class moa.streams.generators.cd.AbstractConceptDriftGenerator
ClusterGenerator - Class in moa.clusterers
ClusterGenerator() - Constructor for class moa.clusterers.ClusterGenerator
Clustering - Class in moa.cluster
Clustering() - Constructor for class moa.cluster.Clustering
Clustering(Cluster[]) - Constructor for class moa.cluster.Clustering
Clustering(List<? extends Instance>) - Constructor for class moa.cluster.Clustering
Clustering(ArrayList<DataPoint>, double, int) - Constructor for class moa.cluster.Clustering
Clustering(AutoExpandVector<Cluster>) - Constructor for class moa.cluster.Clustering
clustering - Variable in class moa.clusterers.AbstractClusterer
ClusteringAlgoPanel - Class in moa.gui.clustertab
ClusteringAlgoPanel() - Constructor for class moa.gui.clustertab.ClusteringAlgoPanel
ClusteringEvalPanel - Class in moa.gui.clustertab
ClusteringEvalPanel() - Constructor for class moa.gui.clustertab.ClusteringEvalPanel: Creates new form ClusteringEvalPanel
ClusteringSetupTab - Class in moa.gui.clustertab
ClusteringSetupTab() - Constructor for class moa.gui.clustertab.ClusteringSetupTab: Creates new form ClusteringSetupTab
ClusteringStream - Class in moa.streams.clustering
ClusteringStream() - Constructor for class moa.streams.clustering.ClusteringStream
ClusteringTabPanel - Class in moa.gui.clustertab
ClusteringTabPanel() - Constructor for class moa.gui.clustertab.ClusteringTabPanel: Creates new form ClusterTab
ClusteringVisualEvalPanel - Class in moa.gui.clustertab
ClusteringVisualEvalPanel() - Constructor for class moa.gui.clustertab.ClusteringVisualEvalPanel: Creates new form ClusteringEvalPanel
ClusteringVisualTab - Class in moa.gui.clustertab
ClusteringVisualTab() - Constructor for class moa.gui.clustertab.ClusteringVisualTab: Creates new form ClusteringVisualTab
ClusterPanel - Class in moa.gui.visualization
ClusterPanel(SphereCluster, Color, StreamPanel) - Constructor for class moa.gui.visualization.ClusterPanel: Creates new form ObjectPanel
clusterRemoveOption - Variable in class moa.clusterers.ClusterGenerator
Clustream - Class in moa.clusterers.clustream: Citation: CluStream: Charu C.
Clustream() - Constructor for class moa.clusterers.clustream.Clustream
ClustreamKernel - Class in moa.clusterers.clustream
ClustreamKernel(Instance, int, long, double, int) - Constructor for class moa.clusterers.clustream.ClustreamKernel
ClustreamKernel(ClustreamKernel, double, int) - Constructor for class moa.clusterers.clustream.ClustreamKernel
ClusTree - Class in moa.clusterers.clustree: Citation: ClusTree: Philipp Kranen, Ira Assent, Corinna Baldauf, Thomas Seidl: The ClusTree: indexing micro-clusters for anytime stream mining.
ClusTree() - Constructor for class moa.clusterers.clustree.ClusTree
CMM - Class in moa.evaluation
CMM() - Constructor for class moa.evaluation.CMM
CMM_GTAnalysis - Class in moa.evaluation
CMM_GTAnalysis(Clustering, ArrayList<DataPoint>, boolean) - Constructor for class moa.evaluation.CMM_GTAnalysis
CMM_GTAnalysis.CMMPoint - Class in moa.evaluation: Wrapper class for data points to store CMM relevant attributes
CMM_GTAnalysis.CMMPoint(DataPoint, int) - Constructor for class moa.evaluation.CMM_GTAnalysis.CMMPoint
CMM_GTAnalysis.GTCluster - Class in moa.evaluation: Main class to model the new clusters that will be the output of the cluster analysis
CobWeb - Class in moa.clusterers: Class implementing the Cobweb and Classit clustering algorithms.
CobWeb() - Constructor for class moa.clusterers.CobWeb
col - Variable in class moa.gui.visualization.ClusterPanel
col - Variable in class moa.gui.visualization.OutlierPanel
col - Variable in class moa.gui.visualization.PointPanel
ColorArray - Class in moa.clusterers.macro
ColorArray() - Constructor for class moa.clusterers.macro.ColorArray
ColorObject - Class in moa.clusterers.macro
ColorObject(String, Color) - Constructor for class moa.clusterers.macro.ColorObject
colour - Variable in class moa.gui.LineGraphViewPanel.PlotLine
columnKappa - Variable in class moa.evaluation.BasicClassificationPerformanceEvaluator
columnKappa - Variable in class moa.evaluation.WindowClassificationPerformanceEvaluator
columnsStatistics - Variable in class moa.streams.filters.ReplacingMissingValuesFilter
combinationOption - Variable in class moa.classifiers.meta.DACC: Combination functions: MAX and WVD (MAX leads to a faster reactivity to the change, WVD is more robust to noise)
combine(SphereCluster) - Method in class moa.cluster.SphereCluster
combSort11(double[], int[]) - Static method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch: sorts the two given arrays.
compareTo(AttributeSplitSuggestion) - Method in class moa.classifiers.core.AttributeSplitSuggestion
compareTo(DACC.Pair) - Method in class moa.classifiers.meta.DACC.Pair
compareTo(StreamObj) - Method in class moa.clusterers.outliers.AbstractC.StreamObj
compareTo(StreamObj) - Method in class moa.clusterers.outliers.Angiulli.StreamObj
compareTo(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
compareTo(MCODBase.EventItem) - Method in class moa.clusterers.outliers.MCOD.MCODBase.EventItem
compareTo(MicroCluster) - Method in class moa.clusterers.outliers.MCOD.MicroCluster
compareTo(StreamObj) - Method in class moa.clusterers.outliers.MCOD.StreamObj
compareTo(MyBaseOutlierDetector.Outlier) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector.Outlier
compareTo(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBNode
compareTo(SimpleCODBase.EventItem) - Method in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase.EventItem
compareTo(StreamObj) - Method in class moa.clusterers.outliers.SimpleCOD.StreamObj
compareTo(Pair<T, U>) - Method in class moa.recommender.rc.utils.Pair
componentHidden(ComponentEvent) - Method in class moa.gui.outliertab.OutlierVisualTab
componentHidden(ComponentEvent) - Method in class moa.gui.visualization.StreamOutlierPanel
componentHidden(ComponentEvent) - Method in class moa.gui.visualization.StreamPanel
componentMoved(ComponentEvent) - Method in class moa.gui.outliertab.OutlierVisualTab
componentMoved(ComponentEvent) - Method in class moa.gui.visualization.StreamOutlierPanel
componentMoved(ComponentEvent) - Method in class moa.gui.visualization.StreamPanel
componentResized(ComponentEvent) - Method in class moa.gui.outliertab.OutlierVisualTab
componentResized(ComponentEvent) - Method in class moa.gui.visualization.StreamOutlierPanel
componentResized(ComponentEvent) - Method in class moa.gui.visualization.StreamPanel
componentShown(ComponentEvent) - Method in class moa.gui.outliertab.OutlierVisualTab
componentShown(ComponentEvent) - Method in class moa.gui.visualization.StreamOutlierPanel
componentShown(ComponentEvent) - Method in class moa.gui.visualization.StreamPanel
ComposedSplitFunction<DATA> - Class in moa.clusterers.outliers.utils.mtree: A split function that is defined by composing a promotion function and a partition function.
ComposedSplitFunction(PromotionFunction<DATA>, PartitionFunction<DATA>) - Constructor for class moa.clusterers.outliers.utils.mtree.ComposedSplitFunction: The constructor of a SplitFunction composed by a PromotionFunction and a PartitionFunction.
compress(long) - Method in class moa.core.GreenwaldKhannaQuantileSummary
compressBuckets() - Method in class moa.classifiers.core.driftdetection.ADWIN
computeAnomalySupervised(RuleClassification, int, Instance) - Method in class moa.classifiers.rules.RuleClassifier
computeAnomalyUnsupervised(RuleClassification, int, Instance) - Method in class moa.classifiers.rules.RuleClassifier
computeBandBoundaries(long) - Static method in class moa.core.GreenwaldKhannaQuantileSummary
computeBranchSplitMerits(double[][]) - Static method in class moa.classifiers.rules.core.splitcriteria.SDRSplitCriterionAMRules
computeCandidateWeight(Classifier, Instances, int) - Method in class moa.classifiers.meta.AccuracyWeightedEnsemble: Computes the weight of a candidate classifier.
computeEntropy(double[]) - Static method in class moa.classifiers.core.splitcriteria.InfoGainSplitCriterion
computeEntropy(double[][]) - Static method in class moa.classifiers.core.splitcriteria.InfoGainSplitCriterion
computeEntropy(double[]) - Static method in class moa.classifiers.core.splitcriteria.InfoGainSplitCriterionMultilabel
computeError(Instance) - Method in class moa.classifiers.rules.core.Rule
computeError(Instance) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
computeError(Instance) - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
computeGini(double[], double) - Static method in class moa.classifiers.core.splitcriteria.GiniSplitCriterion
computeGini(double[]) - Static method in class moa.classifiers.core.splitcriteria.GiniSplitCriterion
computeHoeffdingBound(double, double, double) - Static method in class moa.classifiers.rules.core.RuleActiveLearningNode
ComputeHoeffdingBound(double, double, double) - Method in class moa.classifiers.rules.RuleClassifier
computeHoeffdingBound(double, double, double) - Static method in class moa.classifiers.trees.FIMTDD
computeHoeffdingBound(double, double, double) - Static method in class moa.classifiers.trees.HoeffdingOptionTree
computeHoeffdingBound(double, double, double) - Static method in class moa.classifiers.trees.HoeffdingTree
computeHoeffdingBound(double, double, double) - Static method in class moa.classifiers.trees.ORTO
computeMean(double, int) - Method in class moa.classifiers.rules.RuleClassifier
computeMeritOfExistingSplit(SplitCriterion, double[]) - Method in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
computeMse(Classifier, Instances) - Method in class moa.classifiers.meta.AccuracyUpdatedEnsemble: Computes the MSE of a learner for a given chunk of examples.
computeMseR() - Method in class moa.classifiers.meta.AccuracyUpdatedEnsemble: Computes the MSEr threshold.
computeMseR() - Method in class moa.classifiers.meta.AccuracyWeightedEnsemble: Computes the MSEr threshold.
computeMseR() - Method in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble: Computes the MSEr threshold.
computeProbability(double, double, double) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
computeProbability(double, double, double) - Method in class moa.classifiers.rules.RuleClassifier
computeSD(double[]) - Static method in class moa.classifiers.core.splitcriteria.SDRSplitCriterion
computeSD(double[]) - Static method in class moa.classifiers.core.splitcriteria.VarianceReductionSplitCriterion
computeSD(double, double, long) - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
computeSD(double, double, int) - Method in class moa.classifiers.rules.functions.Perceptron
computeSD(double, double, int) - Method in class moa.classifiers.rules.RuleClassifier
computeSD(double, double, double) - Method in class moa.classifiers.trees.FIMTDD
computeWeight(Classifier, Instances) - Method in class moa.classifiers.meta.AccuracyWeightedEnsemble: Computes the weight of a given classifie.
computeWeight(int, Instance) - Method in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble: Computes the weight of a learner before training a given example.
computeWeightedVote() - Method in class moa.classifiers.rules.core.voting.AbstractErrorWeightedVote
computeWeightedVote() - Method in interface moa.classifiers.rules.core.voting.ErrorWeightedVote: Computes the weighted vote.
computeWeightedVote() - Method in class moa.classifiers.rules.core.voting.InverseErrorWeightedVote
computeWeightedVote() - Method in class moa.classifiers.rules.core.voting.UniformWeightedVote
ConceptDriftGenerator - Interface in moa.streams.generators.cd
ConceptDriftMainTask - Class in moa.tasks
ConceptDriftMainTask() - Constructor for class moa.tasks.ConceptDriftMainTask
ConceptDriftRealStream - Class in moa.streams: Stream generator that adds concept drift to examples in a stream with different classes and attributes.
ConceptDriftRealStream() - Constructor for class moa.streams.ConceptDriftRealStream
ConceptDriftStream - Class in moa.streams: Stream generator that adds concept drift to examples in a stream.
ConceptDriftStream() - Constructor for class moa.streams.ConceptDriftStream
ConceptDriftTabPanel - Class in moa.gui: This panel allows the user to select and configure a task, and run it.
ConceptDriftTabPanel() - Constructor for class moa.gui.ConceptDriftTabPanel
Conditional - Variable in class moa.streams.generators.multilabel.MetaMultilabelGenerator
confidenceChoiceOption - Variable in class moa.clusterers.outliers.AnyOut.AnyOutCore
configureTaskButton - Variable in class moa.gui.conceptdrift.CDTaskManagerPanel
configureTaskButton - Variable in class moa.gui.RegressionTaskManagerPanel
configureTaskButton - Variable in class moa.gui.TaskManagerPanel
confKOption - Variable in class moa.clusterers.outliers.AnyOut.AnyOutCore
connectivity - Variable in class moa.evaluation.CMM_GTAnalysis.CMMPoint: the connectivity of the point to its cluster
constantLearningRatioDecayOption - Variable in class moa.classifiers.rules.AMRulesRegressor
constantLearningRatioDecayOption - Variable in class moa.classifiers.rules.core.Rule.Builder
constantLearningRatioDecayOption - Variable in class moa.classifiers.rules.functions.Perceptron
contains(int, int) - Method in class moa.gui.visualization.ClusterPanel
contains(int, int) - Method in class moa.gui.visualization.OutlierPanel
contextIsCompatible(InstancesHeader, InstancesHeader) - Static method in class moa.classifiers.AbstractClassifier: Returns if two contexts or headers of instances are compatible.

Two contexts are compatible if they follow the following rules:
Rule 1: num classes can increase but never decrease
Rule 2: num attributes can increase but never decrease
Rule 3: num nominal attribute values can increase but never decrease
Rule 4: attribute types must stay in the same order (although class can move; is always skipped over)

Attribute names are free to change, but should always still represent the original attributes.
contextIsCompatible(InstancesHeader, InstancesHeader) - Static method in class moa.clusterers.AbstractClusterer
converter - Variable in class moa.classifiers.multilabel.MultilabelHoeffdingTree
Converter - Class in moa.core.utils: Converter.
Converter() - Constructor for class moa.core.utils.Converter
Converter(int) - Constructor for class moa.core.utils.Converter
convertX(double) - Method in class moa.gui.LineGraphViewPanel.PlotLine
convertY(double) - Method in class moa.gui.LineGraphViewPanel.PlotLine
copy() - Method in class moa.AbstractMOAObject
copy(MOAObject) - Static method in class moa.AbstractMOAObject: This method produces a copy of an object.
copy() - Method in class moa.classifiers.AbstractClassifier
copy() - Method in interface moa.classifiers.Classifier: Produces a copy of this classifier.
copy() - Method in class moa.classifiers.core.driftdetection.AbstractChangeDetector: Produces a copy of this change detector method
copy() - Method in interface moa.classifiers.core.driftdetection.ChangeDetector: Produces a copy of this drift detection method
copy() - Method in interface moa.classifiers.rules.core.voting.ErrorWeightedVote: Creates a copy of the object
copy() - Method in class moa.clusterers.AbstractClusterer
copy() - Method in interface moa.clusterers.Clusterer
copy() - Method in class moa.clusterers.denstream.MicroCluster
copy() - Method in class moa.core.AutoExpandVector
copy() - Method in interface moa.MOAObject: This method produces a copy of this object.
copy() - Method in class moa.options.AbstractOption
copy() - Method in class moa.options.AbstractOptionHandler
copy() - Method in interface moa.options.Option: Gets a copy of this option
copy() - Method in interface moa.options.OptionHandler: This method produces a copy of this object.
copy() - Method in class moa.recommender.rc.utils.DenseVector
copy() - Method in class moa.recommender.rc.utils.SparseVector
copy() - Method in class moa.recommender.rc.utils.Vector
copyClipBoardConfiguration() - Method in class moa.gui.conceptdrift.CDTaskManagerPanel
copyClipBoardConfiguration() - Method in class moa.gui.RegressionTaskManagerPanel
copyClipBoardConfiguration() - Method in class moa.gui.TaskManagerPanel
copyObject(Serializable) - Static method in class moa.core.SerializeUtils
copyrightNotice - Static variable in class moa.core.Globals
copyStatistics(FIMTDD.Node) - Method in class moa.classifiers.trees.FIMTDD.Node
coresetsize - Variable in class moa.clusterers.streamkm.StreamKM
correctlyClassifies(Instance) - Method in class moa.classifiers.AbstractClassifier
correctlyClassifies(Instance) - Method in interface moa.classifiers.Classifier: Gets whether this classifier correctly classifies an instance.
correctlyInitialized() - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter: Checks whether an object of this class has been correctly initialized.
CorrectWeight - Variable in class moa.classifiers.trees.AdaHoeffdingOptionTree.AdaLearningNode
costLabeling - Variable in class moa.classifiers.active.ActiveClassifier
costLabelingRandom - Variable in class moa.classifiers.active.ActiveClassifier
costOfPoint(int, Point[]) - Method in class moa.clusterers.streamkm.Point: Computes the cost of this point with the given array of centres centres[] (of size k)
costOfPointToCenter(Point) - Method in class moa.clusterers.streamkm.Point: Computes the cost of this point with centre centre
count_after - Variable in class moa.clusterers.outliers.Angiulli.ApproxSTORM.ISBNodeAppr
count_after - Variable in class moa.clusterers.outliers.Angiulli.ExactSTORM.ISBNodeExact
count_after - Variable in class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
count_after - Variable in class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBNode
count_before - Variable in class moa.clusterers.outliers.Angiulli.ApproxSTORM.ISBNodeAppr
countLeaves() - Method in class moa.classifiers.trees.FIMTDD.Node
countLeaves() - Method in class moa.classifiers.trees.FIMTDD.SplitNode
CountPrecNeighs(Long) - Method in class moa.clusterers.outliers.Angiulli.ExactSTORM.ISBNodeExact
CountPrecNeighs(Long) - Method in class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
CountPrecNeighs(Long) - Method in class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBNode
countRatingsItem(int) - Method in class moa.recommender.rc.data.impl.MemRecommenderData
countRatingsItem(int) - Method in interface moa.recommender.rc.data.RecommenderData
countRatingsUser(int) - Method in class moa.recommender.rc.data.impl.MemRecommenderData
countRatingsUser(int) - Method in interface moa.recommender.rc.data.RecommenderData
createCustomEditor() - Method in class weka.gui.MOAClassOptionEditor: Creates the custom editor.
createLabelledOptionComponentListPanel(Option[], List<OptionEditComponent>) - Static method in class moa.gui.OptionsConfigurationPanel
createNewClassifier(Instance) - Method in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble: Processes a chunk.
createRule(Instance) - Method in class moa.classifiers.rules.RuleClassifier
createTemplate(Instances) - Method in class moa.core.utils.Converter
createWekaClassifier(String[]) - Method in class moa.classifiers.meta.WEKAClassifier
cumulativeSum - Variable in class moa.classifiers.rules.driftdetection.PageHinkleyTest
curItemID() - Method in interface moa.recommender.dataset.Dataset
curItemID() - Method in class moa.recommender.dataset.impl.FlixsterDataset
curItemID() - Method in class moa.recommender.dataset.impl.JesterDataset
curItemID() - Method in class moa.recommender.dataset.impl.MovielensDataset
curRating() - Method in interface moa.recommender.dataset.Dataset
curRating() - Method in class moa.recommender.dataset.impl.FlixsterDataset
curRating() - Method in class moa.recommender.dataset.impl.JesterDataset
curRating() - Method in class moa.recommender.dataset.impl.MovielensDataset
currentActivityDescription - Variable in class moa.tasks.StandardTaskMonitor
currentActivityFractionComplete - Variable in class moa.tasks.StandardTaskMonitor
currentChunk - Variable in class moa.classifiers.meta.AccuracyUpdatedEnsemble: Current chunk of instances.
currentChunk - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble
currentLength() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborList: Gets the current length of the list.
currentList - Variable in class moa.options.ListOption
currentStatus - Variable in class moa.tasks.TaskThread
currentTask - Variable in class moa.gui.conceptdrift.CDTaskManagerPanel
currentTask - Variable in class moa.gui.RegressionTaskManagerPanel
currentTask - Variable in class moa.gui.TaskManagerPanel
currentVal - Variable in class moa.options.FloatOption
currentVal - Variable in class moa.options.IntOption
currentVal - Variable in class moa.options.StringOption
currentValue - Variable in class moa.options.AbstractClassOption: The current object
currentWindow - Variable in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble: Current window of instance class values.
curUserID() - Method in interface moa.recommender.dataset.Dataset
curUserID() - Method in class moa.recommender.dataset.impl.FlixsterDataset
curUserID() - Method in class moa.recommender.dataset.impl.JesterDataset
curUserID() - Method in class moa.recommender.dataset.impl.MovielensDataset
curve - Variable in class moa.gui.LineGraphViewPanel.PlotLine
CusumDM - Class in moa.classifiers.core.driftdetection: Drift detection method based in Cusum
CusumDM() - Constructor for class moa.classifiers.core.driftdetection.CusumDM
cut_point - Variable in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserver.Node
cut_point - Variable in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserverRegression.Node
cut_point - Variable in class moa.classifiers.core.attributeclassobservers.FIMTDDNumericAttributeClassObserver.Node
cutoffOption - Variable in class moa.clusterers.CobWeb

D

DACC - Class in moa.classifiers.meta: Dynamic Adaptation to Concept Changes.
DACC() - Constructor for class moa.classifiers.meta.DACC
DACC.Pair - Class in moa.classifiers.meta: This helper class is used to sort an array of pairs of integers: val and index.
DACC.Pair(double, int) - Constructor for class moa.classifiers.meta.DACC.Pair
data - Variable in class moa.clusterers.clustree.Entry: The actual entry data.
data - Variable in class moa.clusterers.outliers.utils.mtree.MTree.ResultItem: A nearest-neighbor.
data - Variable in class moa.recommender.rc.predictor.impl.BaselinePredictor
data - Variable in class moa.recommender.rc.predictor.impl.BRISMFPredictor
DataObject - Class in moa.clusterers.outliers.AnyOut.util: This object encapsulates a data point.
DataObject(int, Instance) - Constructor for class moa.clusterers.outliers.AnyOut.util.DataObject: Standard constructor for DataObject.
dataOption - Variable in class moa.recommender.predictor.BaselinePredictor
dataOption - Variable in class moa.recommender.predictor.BRISMFPredictor
DataPoint - Class in moa.gui.visualization
DataPoint(Instance, Integer) - Constructor for class moa.gui.visualization.DataPoint
dataset - Variable in class moa.classifiers.meta.RandomRules
DataSet - Class in moa.clusterers.outliers.AnyOut.util: A set of DataObjects.
DataSet(int) - Constructor for class moa.clusterers.outliers.AnyOut.util.DataSet: Creates an empty set.
DataSet(DataObject) - Constructor for class moa.clusterers.outliers.AnyOut.util.DataSet: Creates a Set with only the given object.
Dataset - Interface in moa.recommender.dataset
datasetOption - Variable in class moa.tasks.EvaluateOnlineRecommender
DBScan - Class in moa.clusterers.macro.dbscan
DBScan(Clustering, double, int) - Constructor for class moa.clusterers.macro.dbscan.DBScan
DDM - Class in moa.classifiers.core.driftdetection: Drift detection method based in DDM method of Joao Gama SBIA 2004.
DDM() - Constructor for class moa.classifiers.core.driftdetection.DDM
DDM_INCONTROL_LEVEL - Static variable in class moa.classifiers.drift.DriftDetectionMethodClassifier
DDM_OUTCONTROL_LEVEL - Static variable in class moa.classifiers.drift.DriftDetectionMethodClassifier
DDM_WARNING_LEVEL - Static variable in class moa.classifiers.drift.DriftDetectionMethodClassifier
ddmLevel - Variable in class moa.classifiers.drift.DriftDetectionMethodClassifier
deactivateAllLeaves() - Method in class moa.classifiers.trees.HoeffdingOptionTree
deactivateAllLeaves() - Method in class moa.classifiers.trees.HoeffdingTree
deactivateLearningNode(HoeffdingTree.ActiveLearningNode, HoeffdingTree.SplitNode, int) - Method in class moa.classifiers.multilabel.MultilabelHoeffdingTree
deactivateLearningNode(HoeffdingOptionTree.ActiveLearningNode, HoeffdingOptionTree.SplitNode, int) - Method in class moa.classifiers.trees.HoeffdingOptionTree
deactivateLearningNode(HoeffdingTree.ActiveLearningNode, HoeffdingTree.SplitNode, int) - Method in class moa.classifiers.trees.HoeffdingTree
debug(String, int) - Method in class moa.classifiers.rules.AbstractAMRules: Print to console
debug(String, int) - Method in class moa.classifiers.rules.core.Rule
debug(String, int) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
debug - Variable in class moa.evaluation.CMM: enable/disable debug mode
debuganomaly(Instance, double, double, double) - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
decay_rate - Variable in class moa.gui.visualization.ClusterPanel
decay_rate - Variable in class moa.gui.visualization.OutlierPanel
decayHorizonOption - Variable in class moa.streams.clustering.ClusteringStream
decayRate - Variable in class moa.gui.visualization.PointPanel
decayThreshold - Variable in class moa.gui.visualization.PointPanel
decayThresholdOption - Variable in class moa.streams.clustering.ClusteringStream
decisionNodeCount - Variable in class moa.classifiers.trees.HoeffdingOptionTree
decisionNodeCount - Variable in class moa.classifiers.trees.HoeffdingTree
DecisionStump - Class in moa.classifiers.trees: Decision trees of one level.
Parameters:
DecisionStump() - Constructor for class moa.classifiers.trees.DecisionStump
decrCutPoint - Variable in class moa.classifiers.core.driftdetection.HDDM_W_Test
default_color - Variable in class moa.gui.visualization.ClusterPanel
default_color - Variable in class moa.gui.visualization.OutlierPanel
default_color - Variable in class moa.gui.visualization.PointPanel
DEFAULT_MIN_NODE_CAPACITY - Static variable in class moa.clusterers.outliers.utils.mtree.MTree: The default minimum capacity of nodes in an M-Tree, when not specified in the constructor call.
defaultCLIString - Variable in class moa.options.AbstractClassOption: The default command line interface text.
defaultFileExtension - Variable in class moa.options.FileOption
defaultList - Variable in class moa.options.ListOption
defaultOptionIndex - Variable in class moa.options.MultiChoiceOption
defaultRule - Variable in class moa.classifiers.rules.AbstractAMRules
defaultVal - Variable in class moa.options.FloatOption
defaultVal - Variable in class moa.options.IntOption
defaultVal - Variable in class moa.options.StringOption
defineDataFormat() - Method in class weka.datagenerators.classifiers.classification.MOA: Initializes the format for the dataset produced.
delay - Variable in class moa.classifiers.core.driftdetection.AbstractChangeDetector: Delay in detecting change
delay - Variable in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
deleteElement() - Method in class moa.classifiers.core.driftdetection.ADWIN
deleteMergeableTupleMostFull() - Method in class moa.core.GreenwaldKhannaQuantileSummary
deleteNode(HoeffdingTree.Node, int) - Method in class moa.classifiers.trees.ASHoeffdingTree
deleteScriptsOption - Variable in class moa.tasks.Plot: Determines whether to delete gnuplot scripts after plotting.
deleteSelectedTasks() - Method in class moa.gui.conceptdrift.CDTaskManagerPanel
deleteSelectedTasks() - Method in class moa.gui.RegressionTaskManagerPanel
deleteSelectedTasks() - Method in class moa.gui.TaskManagerPanel
deleteTaskButton - Variable in class moa.gui.conceptdrift.CDTaskManagerPanel
deleteTaskButton - Variable in class moa.gui.RegressionTaskManagerPanel
deleteTaskButton - Variable in class moa.gui.TaskManagerPanel
deleteTuple(int) - Method in class moa.core.GreenwaldKhannaQuantileSummary
deleteTupleMostFull() - Method in class moa.core.GreenwaldKhannaQuantileSummary
DELTA - Static variable in class moa.classifiers.core.driftdetection.ADWIN
delta - Variable in class moa.core.GreenwaldKhannaQuantileSummary.Tuple
deltaAdwinOption - Variable in class moa.classifiers.core.driftdetection.ADWINChangeDetector
deltaAdwinOption - Variable in class moa.classifiers.meta.LeveragingBag
deltaAdwinOption - Variable in class moa.classifiers.meta.LimAttClassifier
deltaAdwinOption - Variable in class moa.classifiers.meta.OzaBoostAdwin
deltaOption - Variable in class moa.classifiers.core.driftdetection.CusumDM
deltaOption - Variable in class moa.classifiers.core.driftdetection.PageHinkleyDM
deltaOption - Variable in class moa.classifiers.core.driftdetection.SeqDrift1ChangeDetector
deltaSeqDrift2Option - Variable in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector
deltaWarningOption - Variable in class moa.classifiers.core.driftdetection.SeqDrift1ChangeDetector
DenseMicroCluster - Class in moa.clusterers.macro.dbscan
DenseMicroCluster(CFCluster) - Constructor for class moa.clusterers.macro.dbscan.DenseMicroCluster
DenseVector - Class in moa.recommender.rc.utils
DenseVector() - Constructor for class moa.recommender.rc.utils.DenseVector
DenseVector(ArrayList<Double>) - Constructor for class moa.recommender.rc.utils.DenseVector
DenseVector.DenseVectorIterator - Class in moa.recommender.rc.utils
DenseVector.DenseVectorIterator() - Constructor for class moa.recommender.rc.utils.DenseVector.DenseVectorIterator
densityRangeOption - Variable in class moa.streams.clustering.RandomRBFGeneratorEvents
describeConditionForBranch(int, InstancesHeader) - Method in class moa.classifiers.core.conditionaltests.InstanceConditionalTest: Gets the text that describes the condition of a branch.
describeConditionForBranch(int, InstancesHeader) - Method in class moa.classifiers.core.conditionaltests.NominalAttributeBinaryTest
describeConditionForBranch(int, InstancesHeader) - Method in class moa.classifiers.core.conditionaltests.NominalAttributeMultiwayTest
describeConditionForBranch(int, InstancesHeader) - Method in class moa.classifiers.core.conditionaltests.NumericAttributeBinaryTest
describeConditionForBranch(int, InstancesHeader) - Method in class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
describeSubtree(FIMTDD, StringBuilder, int) - Method in class moa.classifiers.trees.FIMTDD.LeafNode
describeSubtree(FIMTDD, StringBuilder, int) - Method in class moa.classifiers.trees.FIMTDD.Node
describeSubtree(FIMTDD, StringBuilder, int) - Method in class moa.classifiers.trees.FIMTDD.SplitNode
describeSubtree(HoeffdingOptionTree, StringBuilder, int) - Method in class moa.classifiers.trees.HoeffdingOptionTree.Node
describeSubtree(HoeffdingOptionTree, StringBuilder, int) - Method in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
describeSubtree(HoeffdingTree, StringBuilder, int) - Method in class moa.classifiers.trees.HoeffdingTree.Node
describeSubtree(HoeffdingTree, StringBuilder, int) - Method in class moa.classifiers.trees.HoeffdingTree.SplitNode
detectMeanIncrement(HDDM_W_Test.SampleInfo, HDDM_W_Test.SampleInfo, double) - Method in class moa.classifiers.core.driftdetection.HDDM_W_Test
determineAssignments(KDTreeNode, Instances, int[], int[], double) - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Assigns instances to the current centers called candidates.
determineClass(double, double, int, int, int, int, double, int, double) - Method in interface moa.streams.generators.AgrawalGenerator.ClassFunction
determineClass(double, double, double) - Method in interface moa.streams.generators.SEAGenerator.ClassFunction
determineClass(int, int, int) - Method in interface moa.streams.generators.STAGGERGenerator.ClassFunction
determineClusterCentreKMeans(int, Point[]) - Method in class moa.clusterers.streamkm.Point: Computes the index of the centre nearest to this point with the given array of centres centres[] (of size k)
determineNumberOfClusters() - Method in class moa.clusterers.CobWeb: determines the number of clusters if necessary
difference(int, double, double) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Computes the difference between two given attribute values.
dimension() - Method in class moa.cluster.Clustering
dimension - Variable in class moa.clusterers.streamkm.StreamKM
dimensions() - Method in class moa.clusterers.outliers.AbstractC.StreamObj
dimensions() - Method in class moa.clusterers.outliers.Angiulli.StreamObj
dimensions() - Method in class moa.clusterers.outliers.MCOD.MicroCluster
dimensions() - Method in class moa.clusterers.outliers.MCOD.StreamObj
dimensions() - Method in class moa.clusterers.outliers.SimpleCOD.StreamObj
dimensions() - Method in interface moa.clusterers.outliers.utils.mtree.DistanceFunctions.EuclideanCoordinate: The number of dimensions.
direction - Variable in class moa.gui.visualization.ClusterPanel
directionForBestTree() - Method in class moa.classifiers.trees.ORTO.OptionNode
disableAttribute(int) - Method in class moa.classifiers.multilabel.HoeffdingTreeClassifLeaves.LearningNodeClassifier
disableAttribute(int) - Method in class moa.classifiers.multilabel.MultilabelHoeffdingTree.MultilabelLearningNodeClassifier
disableAttribute(int) - Method in class moa.classifiers.trees.HoeffdingOptionTree.ActiveLearningNode
disableAttribute(int) - Method in class moa.classifiers.trees.HoeffdingOptionTree.LearningNodeNB
disableAttribute(int) - Method in class moa.classifiers.trees.HoeffdingTree.ActiveLearningNode
disableAttribute(int) - Method in class moa.classifiers.trees.HoeffdingTree.LearningNodeNB
disableAttribute(int) - Method in class moa.classifiers.trees.LimAttHoeffdingTree.LearningNodeNB
disableAttribute(int) - Method in class moa.classifiers.trees.ORTO.ActiveLearningNode
disableAttribute(int) - Method in class moa.classifiers.trees.RandomHoeffdingTree.LearningNodeNB
disableChangeDetection() - Method in class moa.classifiers.trees.FIMTDD.Node
disableChangeDetection() - Method in class moa.classifiers.trees.FIMTDD.SplitNode
disableRefresh() - Method in class moa.gui.PreviewPanel
disableUpdates - Variable in class moa.recommender.rc.data.AbstractRecommenderData
disableUpdates(boolean) - Method in class moa.recommender.rc.data.AbstractRecommenderData
disableUpdates(boolean) - Method in interface moa.recommender.rc.data.RecommenderData
discardModel(int) - Method in class moa.classifiers.meta.AccuracyWeightedEnsemble: Removes the classifier at a given index from the model, thus decreasing the models size.
discardModel(int) - Method in class moa.classifiers.meta.DACC: Resets a classifier in the ensemble
discardModel(int) - Method in class moa.classifiers.meta.WeightedMajorityAlgorithm
discoverOptionsViaReflection() - Method in class moa.options.AbstractOptionHandler: Gets the options of this class via reflection.
DiscreteAttributeClassObserver - Interface in moa.classifiers.core.attributeclassobservers: Interface for observing the class data distribution for a discrete (nominal) attribute.
distance(Instance, Instance) - Method in interface moa.classifiers.lazy.neighboursearch.DistanceFunction: Calculates the distance between two instances.
distance(Instance, Instance, double) - Method in interface moa.classifiers.lazy.neighboursearch.DistanceFunction: Calculates the distance between two instances.
distance(Instance, Instance) - Method in class moa.classifiers.lazy.neighboursearch.EuclideanDistance: Calculates the distance between two instances.
distance - Variable in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.MyHeapElement: the distance of this element.
distance(Instance, Instance) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Calculates the distance between two instances.
distance(Instance, Instance, double) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Calculates the distance between two instances.
distance - Variable in class moa.clusterers.outliers.AbstractC.ISBIndex.ISBSearchResult
distance - Variable in class moa.clusterers.outliers.Angiulli.ISBIndex.ISBSearchResult
distance - Variable in class moa.clusterers.outliers.MCOD.ISBIndex.ISBSearchResult
distance - Variable in class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBSearchResult
distance - Variable in class moa.clusterers.outliers.utils.mtree.MTree.ResultItem: The distance from the nearest-neighbor to the query data object parameter.
DistanceFunction - Interface in moa.classifiers.lazy.neighboursearch: Interface for any class that can compute and return distances between two instances.
DistanceFunction<DATA> - Interface in moa.clusterers.outliers.utils.mtree: An object that can calculate the distance between two data objects.
distanceFunction - Variable in class moa.clusterers.outliers.utils.mtree.MTree
DistanceFunctions - Class in moa.clusterers.outliers.utils.mtree: Some pre-defined implementations of distance functions.
DistanceFunctions.EuclideanCoordinate - Interface in moa.clusterers.outliers.utils.mtree: An interface to represent coordinates in Euclidean spaces.
distanceFunctionTipText() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch: Returns the tip text for this property.
distanceToHrect(KDTreeNode, Instance) - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Returns the distance between a point and an hyperrectangle.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.MOA: Predicts the class memberships for a given instance.
dloss(double) - Method in class moa.classifiers.functions.SGD
dloss(double) - Method in class moa.classifiers.functions.SGDMultiClass
dloss(double) - Method in class moa.classifiers.functions.SPegasos
doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.EvaluateClustering
doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.EvaluateConceptDrift
doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.EvaluateInterleavedChunks
doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.EvaluateInterleavedTestThenTrain
doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.EvaluateModel
doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.EvaluateModelRegression
doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.EvaluateOnlineRecommender
doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.EvaluatePeriodicHeldOutTest
doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.EvaluatePrequential
doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.EvaluatePrequentialRegression
doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.LearnModel
doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.LearnModelRegression
doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.MainTask: This method performs this task.
doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.MeasureStreamSpeed
doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.Plot
doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.RunStreamTasks
doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.RunTasks
doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.WriteStreamToARFFFile
doNaiveBayesPrediction(Instance, DoubleVector, AutoExpandVector<AttributeClassObserver>) - Static method in class moa.classifiers.bayes.NaiveBayes
doNaiveBayesPredictionLog(Instance, DoubleVector, AutoExpandVector<AttributeClassObserver>, AutoExpandVector<AttributeClassObserver>) - Static method in class moa.classifiers.bayes.NaiveBayes
dontNormalizeTipText() - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Returns the tip text for this property.
DoTask - Class in moa: Class for running a MOA task from the command line.
DoTask() - Constructor for class moa.DoTask
doTask() - Method in class moa.tasks.AbstractTask
doTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.AbstractTask
doTask() - Method in interface moa.tasks.Task: This method performs this task, when TaskMonitor and ObjectRepository are no needed.
doTask(TaskMonitor, ObjectRepository) - Method in interface moa.tasks.Task: This method performs this task.
doTaskImpl(TaskMonitor, ObjectRepository) - Method in class moa.tasks.AbstractTask: This method performs this task.
doTaskImpl(TaskMonitor, ObjectRepository) - Method in class moa.tasks.CacheShuffledStream
doTaskImpl(TaskMonitor, ObjectRepository) - Method in class moa.tasks.MainTask
dotProd(Instance, DoubleVector, int) - Static method in class moa.classifiers.functions.SGD
dotProd(Instance, DoubleVector, int) - Static method in class moa.classifiers.functions.SGDMultiClass
dotProd(Instance, double[], int) - Static method in class moa.classifiers.functions.SPegasos
dotProduct(Vector) - Method in class moa.recommender.rc.utils.Vector
DOUBLE_ADD - Static variable in class moa.clusterers.clustree.util.SimpleBudget
DOUBLE_DIV - Static variable in class moa.clusterers.clustree.util.SimpleBudget
DOUBLE_MULT - Static variable in class moa.clusterers.clustree.util.SimpleBudget
doubleAddition() - Method in interface moa.clusterers.clustree.util.Budget: Inform the Budget class that a double addition has been performed by the tree.
doubleAddition(int) - Method in interface moa.clusterers.clustree.util.Budget: Inform the Budget that a certain number of double additions have been performed.
doubleAddition() - Method in class moa.clusterers.clustree.util.SimpleBudget
doubleAddition(int) - Method in class moa.clusterers.clustree.util.SimpleBudget
doubleDivision() - Method in interface moa.clusterers.clustree.util.Budget: Inform the Budget class that a double division has been performed by the tree.
doubleDivision(int) - Method in interface moa.clusterers.clustree.util.Budget: Inform the Budget that a certain number of double divisions have been performed.
doubleDivision() - Method in class moa.clusterers.clustree.util.SimpleBudget
doubleDivision(int) - Method in class moa.clusterers.clustree.util.SimpleBudget
doubleMultiplication() - Method in interface moa.clusterers.clustree.util.Budget: Inform the Budget class that a double multiplicaton has been performed by the tree.
doubleMultiplication(int) - Method in interface moa.clusterers.clustree.util.Budget: Inform the Budget that a certain number of double multiplications have been performed.
doubleMultiplication() - Method in class moa.clusterers.clustree.util.SimpleBudget
doubleMultiplication(int) - Method in class moa.clusterers.clustree.util.SimpleBudget
doubleToCLIString(double) - Static method in class moa.options.FloatOption
doubleToString(double, int) - Static method in class moa.core.StringUtils
doubleToString(double, int, int) - Static method in class moa.core.StringUtils
DoubleVector - Class in moa.core: Vector of double numbers with some utilities.
DoubleVector() - Constructor for class moa.core.DoubleVector
DoubleVector(double[]) - Constructor for class moa.core.DoubleVector
DoubleVector(DoubleVector) - Constructor for class moa.core.DoubleVector
downheap() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.MyHeap: performs downheap operation for the heap to maintian its properties.
drawClusterings(List<DataPoint>, List<DataPoint>) - Method in class moa.gui.visualization.RunVisualizer
drawEvent(OutlierEvent, boolean) - Method in class moa.gui.visualization.StreamOutlierPanel
drawGTClustering(Clustering, List<DataPoint>, Color) - Method in class moa.gui.visualization.StreamPanel
drawMacroClustering(Clustering, List<DataPoint>, Color) - Method in class moa.gui.visualization.StreamPanel
drawMicroClustering(Clustering, List<DataPoint>, Color) - Method in class moa.gui.visualization.StreamPanel
drawOnCanvas(Graphics2D) - Method in class moa.gui.visualization.ClusterPanel
drawOnCanvas(Graphics2D) - Method in class moa.gui.visualization.OutlierPanel
drawOnCanvas(Graphics2D) - Method in class moa.gui.visualization.PointPanel
drawOutliers(Vector<MyBaseOutlierDetector.Outlier>, Color) - Method in class moa.gui.visualization.StreamOutlierPanel
drawPoint(DataPoint, boolean, boolean) - Method in class moa.gui.visualization.StreamOutlierPanel
drawPoint(DataPoint) - Method in class moa.gui.visualization.StreamPanel
driftConfidence - Variable in class moa.classifiers.core.driftdetection.HDDM_W_Test
driftConfidenceOption - Variable in class moa.classifiers.core.driftdetection.HDDM_A_Test
driftConfidenceOption - Variable in class moa.classifiers.core.driftdetection.HDDM_W_Test
driftDetectionMethod - Variable in class moa.classifiers.drift.DriftDetectionMethodClassifier
driftDetectionMethod - Variable in class moa.learners.ChangeDetectorLearner
DriftDetectionMethodClassifier - Class in moa.classifiers.drift: Class for handling concept drift datasets with a wrapper on a classifier.
DriftDetectionMethodClassifier() - Constructor for class moa.classifiers.drift.DriftDetectionMethodClassifier
driftDetectionMethodOption - Variable in class moa.classifiers.drift.DriftDetectionMethodClassifier
driftDetectionMethodOption - Variable in class moa.learners.ChangeDetectorLearner
DriftDetectionOption - Variable in class moa.classifiers.rules.AbstractAMRules
driftInstance - Variable in class moa.streams.ConceptDriftRealStream
driftStream - Variable in class moa.streams.ConceptDriftRealStream
driftStream - Variable in class moa.streams.ConceptDriftStream
driftstreamOption - Variable in class moa.streams.ConceptDriftRealStream
driftstreamOption - Variable in class moa.streams.ConceptDriftStream
dumpFileOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree
dumpFileOption - Variable in class moa.tasks.EvaluateClustering
dumpFileOption - Variable in class moa.tasks.EvaluateConceptDrift
dumpFileOption - Variable in class moa.tasks.EvaluateInterleavedChunks: Allows to define the output file name and location.
dumpFileOption - Variable in class moa.tasks.EvaluateInterleavedTestThenTrain
dumpFileOption - Variable in class moa.tasks.EvaluatePeriodicHeldOutTest
dumpFileOption - Variable in class moa.tasks.EvaluatePrequential
dumpFileOption - Variable in class moa.tasks.EvaluatePrequentialRegression

E

EDDM - Class in moa.classifiers.core.driftdetection: Drift detection method based in EDDM method of Manuel Baena et al.
EDDM() - Constructor for class moa.classifiers.core.driftdetection.EDDM
editButton - Variable in class moa.gui.ClassOptionEditComponent
editButton - Variable in class moa.gui.ClassOptionWithNamesEditComponent
editButton - Variable in class moa.gui.WEKAClassOptionEditComponent
editComponents - Variable in class moa.gui.clustertab.ClusteringAlgoPanel
editComponents - Variable in class moa.gui.OptionsConfigurationPanel
editComponents - Variable in class moa.gui.outliertab.OutlierAlgoPanel
editedOption - Variable in class moa.gui.ClassOptionEditComponent
editedOption - Variable in class moa.gui.ClassOptionWithNamesEditComponent
editedOption - Variable in class moa.gui.FileOptionEditComponent
editedOption - Variable in class moa.gui.FlagOptionEditComponent
editedOption - Variable in class moa.gui.FloatOptionEditComponent
editedOption - Variable in class moa.gui.IntOptionEditComponent
editedOption - Variable in class moa.gui.MultiChoiceOptionEditComponent
editedOption - Variable in class moa.gui.StringOptionEditComponent
editedOption - Variable in class moa.gui.WEKAClassOptionEditComponent
editObject() - Method in class moa.gui.ClassOptionEditComponent
editObject() - Method in class moa.gui.ClassOptionWithNamesEditComponent
editObject() - Method in class moa.gui.WEKAClassOptionEditComponent
EMProjectedClustering - Class in moa.clusterers.outliers.AnyOut.util: Implements clustering via Expectation Maximization but return a clear partitioning of the data, i.e.
EMProjectedClustering() - Constructor for class moa.clusterers.outliers.AnyOut.util.EMProjectedClustering
emptyBuffer(long, double) - Method in class moa.clusterers.clustree.Entry: Clear the buffer in this entry and return a copy.
EMTopDownTreeBuilder - Class in moa.clusterers.outliers.AnyOut.util
EMTopDownTreeBuilder() - Constructor for class moa.clusterers.outliers.AnyOut.util.EMTopDownTreeBuilder
enableClassMerge - Variable in class moa.evaluation.CMM: enable/disable class merge (main feature of ground truth analysis)
enableModelError - Variable in class moa.evaluation.CMM: enable/disable model error when enabled errors that are caused by the underling cluster model will not be counted
enablePreciseTiming() - Static method in class moa.core.TimingUtils
enableRefresh() - Method in class moa.gui.PreviewPanel
enforceMemoryLimit() - Method in class moa.classifiers.meta.AccuracyUpdatedEnsemble: Checks if the memory limit is exceeded and if so prunes the classifiers in the ensemble.
enforceMemoryLimit() - Method in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble: Checks if the memory limit is exceeded and if so prunes the classifiers in the ensemble.
enforceTrackerLimit() - Method in class moa.classifiers.trees.HoeffdingOptionTree
enforceTrackerLimit() - Method in class moa.classifiers.trees.HoeffdingTree
ensemble - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble
ensemble - Variable in class moa.classifiers.meta.DACC: Ensemble of classifiers
ensemble - Variable in class moa.classifiers.meta.LeveragingBag
ensemble - Variable in class moa.classifiers.meta.LimAttClassifier
ensemble - Variable in class moa.classifiers.meta.OCBoost
ensemble - Variable in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble: Ensemble classifiers.
ensemble - Variable in class moa.classifiers.meta.OnlineSmoothBoost
ensemble - Variable in class moa.classifiers.meta.OzaBag
ensemble - Variable in class moa.classifiers.meta.OzaBagAdwin
ensemble - Variable in class moa.classifiers.meta.OzaBoost
ensemble - Variable in class moa.classifiers.meta.OzaBoostAdwin
ensemble - Variable in class moa.classifiers.meta.RandomRules
ensemble - Variable in class moa.classifiers.meta.WeightedMajorityAlgorithm
ensembleAges - Variable in class moa.classifiers.meta.DACC: Age of classifiers (to compare with maturity age)
EnsembleDriftDetectionMethods - Class in moa.classifiers.core.driftdetection: Ensemble Drift detection method
EnsembleDriftDetectionMethods() - Constructor for class moa.classifiers.core.driftdetection.EnsembleDriftDetectionMethods
ensembleSizeOption - Variable in class moa.classifiers.meta.LeveragingBag
ensembleSizeOption - Variable in class moa.classifiers.meta.OCBoost
ensembleSizeOption - Variable in class moa.classifiers.meta.OnlineSmoothBoost
ensembleSizeOption - Variable in class moa.classifiers.meta.OzaBag
ensembleSizeOption - Variable in class moa.classifiers.meta.OzaBagAdwin
ensembleSizeOption - Variable in class moa.classifiers.meta.OzaBoost
ensembleSizeOption - Variable in class moa.classifiers.meta.OzaBoostAdwin
ensembleSizeOption - Variable in class moa.classifiers.meta.RandomRules
ensembleWeights - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble
ensembleWeights - Variable in class moa.classifiers.meta.DACC: Weights of classifiers
ensembleWeights - Variable in class moa.classifiers.meta.WeightedMajorityAlgorithm
ensembleWindows - Variable in class moa.classifiers.meta.DACC: Evaluation windows (recent classification errors)
entropy(DoubleVector) - Method in class moa.classifiers.rules.RuleClassifier
EntropyCollection - Class in moa.evaluation
EntropyCollection() - Constructor for class moa.evaluation.EntropyCollection
Entry - Class in moa.clusterers.clustree
Entry(int) - Constructor for class moa.clusterers.clustree.Entry: Constructor for the entry.
Entry(int, Node, long, Entry, Node) - Constructor for class moa.clusterers.clustree.Entry: Constructor that creates an Entry that points to the given node.
Entry(int, ClusKernel, long) - Constructor for class moa.clusterers.clustree.Entry: Constructuctor that creates an Entry with an empty buffer and the data given by the Kernel.
Entry(int, ClusKernel, long, Entry, Node) - Constructor for class moa.clusterers.clustree.Entry: extended constructor with containerNode and parentEntry
Entry(Entry) - Constructor for class moa.clusterers.clustree.Entry: Copy constructor.
entryToString(int) - Method in class moa.evaluation.LearningCurve
enumerateMeasures() - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Returns an enumeration of the additional measure names.
EPSILON - Static variable in class moa.clusterers.clustree.ClusKernel: Numeric epsilon.
epsilonOption - Variable in class moa.clusterers.denstream.WithDBSCAN
equals(Object) - Method in class moa.clusterers.outliers.AbstractC.StreamObj
equals(Object) - Method in class moa.clusterers.outliers.Angiulli.StreamObj
equals(Object) - Method in class moa.clusterers.outliers.MCOD.MicroCluster
equals(Object) - Method in class moa.clusterers.outliers.MCOD.StreamObj
equals(Object) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector.Outlier
equals(Object) - Method in class moa.clusterers.outliers.SimpleCOD.StreamObj
equalsPassesTest - Variable in class moa.classifiers.core.conditionaltests.NumericAttributeBinaryTest
equivIndexSizeOption - Variable in class moa.classifiers.meta.ADACC: Threshold for concept equivalence
ERR - Static variable in class moa.classifiers.lazy.neighboursearch.kdtrees.SlidingMidPointOfWidestSide: The floating point error to tolerate in finding the widest rectangular side.
error - Variable in class moa.classifiers.meta.OzaBagASHT
ErrorChange - Variable in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaLearningNode
ErrorChange - Variable in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaSplitNode
errorPrediction - Variable in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
errors - Variable in class moa.classifiers.rules.core.voting.AbstractErrorWeightedVote
errorSum - Variable in class moa.classifiers.rules.functions.TargetMean
ErrorWeightedVote - Interface in moa.classifiers.rules.core.voting: ErrorWeightedVote interface for weighted votes based on estimates of errors.
estimatedRemainingInstances() - Method in class moa.streams.ArffFileStream
estimatedRemainingInstances() - Method in class moa.streams.CachedInstancesStream
estimatedRemainingInstances() - Method in class moa.streams.clustering.FileStream
estimatedRemainingInstances() - Method in class moa.streams.clustering.RandomRBFGeneratorEvents
estimatedRemainingInstances() - Method in class moa.streams.ConceptDriftRealStream
estimatedRemainingInstances() - Method in class moa.streams.ConceptDriftStream
estimatedRemainingInstances() - Method in class moa.streams.FilteredStream
estimatedRemainingInstances() - Method in class moa.streams.filters.AbstractStreamFilter
estimatedRemainingInstances() - Method in class moa.streams.filters.CacheFilter
estimatedRemainingInstances() - Method in class moa.streams.generators.AgrawalGenerator
estimatedRemainingInstances() - Method in class moa.streams.generators.cd.AbstractConceptDriftGenerator
estimatedRemainingInstances() - Method in class moa.streams.generators.HyperplaneGenerator
estimatedRemainingInstances() - Method in class moa.streams.generators.LEDGenerator
estimatedRemainingInstances() - Method in class moa.streams.generators.multilabel.MetaMultilabelGenerator
estimatedRemainingInstances() - Method in class moa.streams.generators.RandomRBFGenerator
estimatedRemainingInstances() - Method in class moa.streams.generators.RandomTreeGenerator
estimatedRemainingInstances() - Method in class moa.streams.generators.SEAGenerator
estimatedRemainingInstances() - Method in class moa.streams.generators.STAGGERGenerator
estimatedRemainingInstances() - Method in class moa.streams.generators.WaveformGenerator
estimatedRemainingInstances() - Method in interface moa.streams.InstanceStream: Gets the estimated number of remaining instances in this stream
estimatedRemainingInstances() - Method in class moa.streams.MultiFilteredStream
estimatedWeight_LessThan_EqualTo_GreaterThan_Value(double) - Method in class moa.core.GaussianEstimator
estimateModelByteSizes() - Method in class moa.classifiers.trees.HoeffdingOptionTree
estimateModelByteSizes() - Method in class moa.classifiers.trees.HoeffdingTree
estimation - Variable in class moa.classifiers.core.driftdetection.AbstractChangeDetector: Prediction for the next value based in previous seen values
estimation - Variable in class moa.evaluation.EWMAClassificationPerformanceEvaluator.Estimator
estimation() - Method in class moa.evaluation.EWMAClassificationPerformanceEvaluator.Estimator
estimation - Variable in class moa.evaluation.FadingFactorClassificationPerformanceEvaluator.Estimator
estimation() - Method in class moa.evaluation.FadingFactorClassificationPerformanceEvaluator.Estimator
estimationErrorWeight - Variable in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaLearningNode
estimationErrorWeight - Variable in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaSplitNode
EUCLIDEAN - Static variable in class moa.clusterers.outliers.utils.mtree.DistanceFunctions: A distance function object that calculates the distance between two euclidean coordinates.
euclidean(DistanceFunctions.EuclideanCoordinate, DistanceFunctions.EuclideanCoordinate) - Static method in class moa.clusterers.outliers.utils.mtree.DistanceFunctions: Calculates the distance between two euclidean coordinates.
EUCLIDEAN_DOUBLE_LIST - Static variable in class moa.clusterers.outliers.utils.mtree.DistanceFunctions: A distance function object that calculates the distance between two coordinates represented by lists of Doubles.
EUCLIDEAN_INTEGER_LIST - Static variable in class moa.clusterers.outliers.utils.mtree.DistanceFunctions: A distance function object that calculates the distance between two coordinates represented by lists of Integers.
EuclideanDistance - Class in moa.classifiers.lazy.neighboursearch: Implementing Euclidean distance (or similarity) function.

One object defines not one distance but the data model in which the distances between objects of that data model can be computed.

Attention: For efficiency reasons the use of consistency checks (like are the data models of the two instances exactly the same), is low.

For more information, see:

Wikipedia.
EuclideanDistance() - Constructor for class moa.classifiers.lazy.neighboursearch.EuclideanDistance: Constructs an Euclidean Distance object, Instances must be still set.
EuclideanDistance(Instances) - Constructor for class moa.classifiers.lazy.neighboursearch.EuclideanDistance: Constructs an Euclidean Distance object and automatically initializes the ranges.
evaluate(Instance) - Method in class moa.classifiers.rules.core.conditionaltests.NominalAttributeBinaryRulePredicate
evaluate(Instance) - Method in class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
evaluate(Instance) - Method in interface moa.classifiers.rules.core.Predicate
evaluate(Instance) - Method in class moa.classifiers.rules.nodes.RuleSplitNode
evaluate(Instance) - Method in class moa.classifiers.rules.Predicates
evaluateClustering(Clustering, Clustering, ArrayList<DataPoint>) - Method in class moa.evaluation.Accuracy
evaluateClustering(Clustering, Clustering, ArrayList<DataPoint>) - Method in class moa.evaluation.ChangeDetectionMeasures
evaluateClustering(Clustering, Clustering, ArrayList<DataPoint>) - Method in class moa.evaluation.CMM
evaluateClustering(Clustering, Clustering, ArrayList<DataPoint>) - Method in class moa.evaluation.EntropyCollection
evaluateClustering(Clustering, Clustering, ArrayList<DataPoint>) - Method in class moa.evaluation.F1
evaluateClustering(Clustering, Clustering, ArrayList<DataPoint>) - Method in class moa.evaluation.General
evaluateClustering(Clustering, Clustering, ArrayList<DataPoint>) - Method in class moa.evaluation.MeasureCollection
evaluateClustering(Clustering, Clustering, ArrayList<DataPoint>) - Method in class moa.evaluation.OutlierPerformance
evaluateClustering(Clustering, Clustering, ArrayList<DataPoint>) - Method in class moa.evaluation.SilhouetteCoefficient
evaluateClustering(Clustering, Clustering, ArrayList<DataPoint>) - Method in class moa.evaluation.SSQ
evaluateClustering(Clustering, Clustering, ArrayList<DataPoint>) - Method in class moa.evaluation.StatisticalCollection
EvaluateClustering - Class in moa.tasks: Task for evaluating a clusterer on a stream.
EvaluateClustering() - Constructor for class moa.tasks.EvaluateClustering
evaluateClusteringPerformance(Clustering, Clustering, ArrayList<DataPoint>) - Method in class moa.evaluation.MeasureCollection
EvaluateConceptDrift - Class in moa.tasks: Task for evaluating a classifier on a stream by testing then training with each example in sequence.
EvaluateConceptDrift() - Constructor for class moa.tasks.EvaluateConceptDrift
EvaluateInterleavedChunks - Class in moa.tasks
EvaluateInterleavedChunks() - Constructor for class moa.tasks.EvaluateInterleavedChunks
EvaluateInterleavedTestThenTrain - Class in moa.tasks: Task for evaluating a classifier on a stream by testing then training with each example in sequence.
EvaluateInterleavedTestThenTrain() - Constructor for class moa.tasks.EvaluateInterleavedTestThenTrain
evaluateMicroClusteringOption - Variable in class moa.clusterers.AbstractClusterer
EvaluateModel - Class in moa.tasks: Task for evaluating a static model on a stream.
EvaluateModel() - Constructor for class moa.tasks.EvaluateModel
EvaluateModel(Classifier, InstanceStream, ClassificationPerformanceEvaluator, int) - Constructor for class moa.tasks.EvaluateModel
EvaluateModelRegression - Class in moa.tasks: Task for evaluating a static model on a stream.
EvaluateModelRegression() - Constructor for class moa.tasks.EvaluateModelRegression
EvaluateModelRegression(Classifier, InstanceStream, ClassificationPerformanceEvaluator, int) - Constructor for class moa.tasks.EvaluateModelRegression
evaluateMultiLabel(ArrayList<double[]>, ArrayList<int[]>, double) - Static method in class moa.core.utils.EvalUtils: Calculate Performance Measures.
EvaluateOnlineRecommender - Class in moa.tasks: Test for evaluating a recommender by training and periodically testing on samples from a rating dataset.
EvaluateOnlineRecommender() - Constructor for class moa.tasks.EvaluateOnlineRecommender
EvaluatePeriodicHeldOutTest - Class in moa.tasks: Task for evaluating a classifier on a stream by periodically testing on a heldout set.
EvaluatePeriodicHeldOutTest() - Constructor for class moa.tasks.EvaluatePeriodicHeldOutTest
EvaluatePrequential - Class in moa.tasks: Task for evaluating a classifier on a stream by testing then training with each example in sequence.
EvaluatePrequential() - Constructor for class moa.tasks.EvaluatePrequential
EvaluatePrequentialRegression - Class in moa.tasks: Task for evaluating a classifier on a stream by testing then training with each example in sequence.
EvaluatePrequentialRegression() - Constructor for class moa.tasks.EvaluatePrequentialRegression
evaluationFrequencyOption - Variable in class moa.streams.clustering.ClusteringStream
evaluationSizeOption - Variable in class moa.classifiers.meta.DACC: Size of the evaluation window for weights computing
evaluatorOption - Variable in class moa.tasks.EvaluateConceptDrift
evaluatorOption - Variable in class moa.tasks.EvaluateInterleavedChunks: Allows to select the classifier performance evaluation method.
evaluatorOption - Variable in class moa.tasks.EvaluateInterleavedTestThenTrain
evaluatorOption - Variable in class moa.tasks.EvaluateModel
evaluatorOption - Variable in class moa.tasks.EvaluateModelRegression
evaluatorOption - Variable in class moa.tasks.EvaluatePeriodicHeldOutTest
evaluatorOption - Variable in class moa.tasks.EvaluatePrequential
evaluatorOption - Variable in class moa.tasks.EvaluatePrequentialRegression
EvalUtils - Class in moa.core.utils: Evaluation Utilities.
EvalUtils() - Constructor for class moa.core.utils.EvalUtils
eventDeleteCreateOption - Variable in class moa.streams.clustering.RandomRBFGeneratorEvents
eventFrequencyOption - Variable in class moa.streams.clustering.RandomRBFGeneratorEvents
eventMergeSplitOption - Variable in class moa.streams.clustering.RandomRBFGeneratorEvents
eventQueue - Variable in class moa.clusterers.outliers.MCOD.MCODBase
eventQueue - Variable in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
events - Variable in class moa.tasks.ConceptDriftMainTask
events - Variable in class moa.tasks.RegressionMainTask
EWMA_Estimator - Variable in class moa.classifiers.core.driftdetection.HDDM_W_Test.SampleInfo
EWMAChartDM - Class in moa.classifiers.core.driftdetection: Drift detection method based in EWMA Charts of Ross, Adams, Tasoulis and Hand 2012
EWMAChartDM() - Constructor for class moa.classifiers.core.driftdetection.EWMAChartDM
EWMAClassificationPerformanceEvaluator - Class in moa.evaluation: Classification evaluator that updates evaluation results using an Exponential Weighted Moving Average.
EWMAClassificationPerformanceEvaluator() - Constructor for class moa.evaluation.EWMAClassificationPerformanceEvaluator
EWMAClassificationPerformanceEvaluator.Estimator - Class in moa.evaluation
EWMAClassificationPerformanceEvaluator.Estimator(double) - Constructor for class moa.evaluation.EWMAClassificationPerformanceEvaluator.Estimator
ExactSTORM - Class in moa.clusterers.outliers.Angiulli
ExactSTORM() - Constructor for class moa.clusterers.outliers.Angiulli.ExactSTORM
ExactSTORM.ISBNodeExact - Class in moa.clusterers.outliers.Angiulli
ExactSTORM.ISBNodeExact(Instance, StreamObj, Long, int) - Constructor for class moa.clusterers.outliers.Angiulli.ExactSTORM.ISBNodeExact
examplesSeen - Variable in class moa.classifiers.trees.FIMTDD.Node
examplesSeen() - Method in class moa.classifiers.trees.FIMTDD.Node
examplesSeen - Variable in class moa.classifiers.trees.ORTO.ActiveLearningNode
examplesSeenAtLastSplitEvaluation - Variable in class moa.classifiers.trees.FIMTDD.LeafNode
examplesSeenAtLastSplitEvaluation() - Method in class moa.classifiers.trees.FIMTDD.LeafNode
examplesSeenAtLastSplitEvaluation - Variable in class moa.classifiers.trees.ORTO.ActiveLearningNode
expandeRule(RuleClassification, Instance, int) - Method in class moa.classifiers.rules.RuleClassifier
expectedType - Variable in class moa.options.ListOption
exponential(double[]) - Method in class moa.classifiers.rules.RuleClassifierNBayes
exportButton - Variable in class moa.gui.TaskTextViewerPanel
exportButton - Variable in class moa.gui.TextViewerPanel
exportCSV(String, ArrayList<ClusterEvent>, MeasureCollection[], int) - Static method in class moa.gui.BatchCmd
exportCSV(String) - Method in class moa.gui.visualization.RunOutlierVisualizer
exportCSV(String) - Method in class moa.gui.visualization.RunVisualizer
exportFileExtension - Static variable in class moa.gui.conceptdrift.CDTaskManagerPanel
exportFileExtension - Static variable in class moa.gui.RegressionTaskManagerPanel
exportFileExtension - Static variable in class moa.gui.TaskManagerPanel
exportFileExtension - Static variable in class moa.gui.TaskTextViewerPanel
exportFileExtension - Static variable in class moa.gui.TextViewerPanel
extendWithOldLabels(Instance) - Method in class moa.classifiers.meta.TemporallyAugmentedClassifier
ExtractMin() - Method in class moa.clusterers.outliers.MCOD.MCODBase.EventQueue
ExtractMin() - Method in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase.EventQueue

F

F1 - Class in moa.evaluation
F1() - Constructor for class moa.evaluation.F1
fadingErrorFactorOption - Variable in class moa.classifiers.rules.functions.TargetMean
fadingFactor - Variable in class moa.classifiers.rules.functions.Perceptron
FadingFactorClassificationPerformanceEvaluator - Class in moa.evaluation: Classification evaluator that updates evaluation results using a fading factor.
FadingFactorClassificationPerformanceEvaluator() - Constructor for class moa.evaluation.FadingFactorClassificationPerformanceEvaluator
FadingFactorClassificationPerformanceEvaluator.Estimator - Class in moa.evaluation
FadingFactorClassificationPerformanceEvaluator.Estimator(double) - Constructor for class moa.evaluation.FadingFactorClassificationPerformanceEvaluator.Estimator
fadingFactorOption - Variable in class moa.classifiers.rules.functions.FadingTargetMean
fadingFactorOption - Variable in class moa.classifiers.rules.functions.Perceptron
FadingTargetMean - Class in moa.classifiers.rules.functions
FadingTargetMean() - Constructor for class moa.classifiers.rules.functions.FadingTargetMean
FailedTaskReport - Class in moa.tasks: Class for reporting a failed task.
FailedTaskReport(Throwable) - Constructor for class moa.tasks.FailedTaskReport
failureReason - Variable in class moa.tasks.FailedTaskReport
featuresOption - Variable in class moa.recommender.predictor.BRISMFPredictor
FILE_PREFIX_STRING - Static variable in class moa.options.AbstractClassOption: The prefix text to use to indicate file.
fileAliasesOption - Variable in class moa.tasks.Plot: Comma separated list of aliases for the input *csv files.
fileExtension - Variable in class moa.gui.FileExtensionFilter
FileExtensionFilter - Class in moa.gui: A filter that is used to restrict the files that are shown.
FileExtensionFilter(String) - Constructor for class moa.gui.FileExtensionFilter
FileOption - Class in moa.options: File option.
FileOption(String, char, String, String, String, boolean) - Constructor for class moa.options.FileOption
fileOption - Variable in class moa.recommender.dataset.impl.FlixsterDataset
fileOption - Variable in class moa.recommender.dataset.impl.JesterDataset
fileOption - Variable in class moa.recommender.dataset.impl.MovielensDataset
FileOptionEditComponent - Class in moa.gui: An OptionEditComponent that lets the user edit a file option.
FileOptionEditComponent(FileOption) - Constructor for class moa.gui.FileOptionEditComponent
fileProgressMonitor - Variable in class moa.streams.ArffFileStream
fileProgressMonitor - Variable in class moa.streams.clustering.FileStream
fileReader - Variable in class moa.streams.ArffFileStream
fileReader - Variable in class moa.streams.clustering.FileStream
FileStream - Class in moa.streams.clustering
FileStream() - Constructor for class moa.streams.clustering.FileStream
filterChain - Variable in class moa.streams.FilteredStream
filterChain - Variable in class moa.streams.MultiFilteredStream
FilteredStream - Class in moa.streams: Class for representing a stream that is filtered.
FilteredStream() - Constructor for class moa.streams.FilteredStream
filterInstanceToLeaf(Instance, HoeffdingTree.SplitNode, int) - Method in class moa.classifiers.trees.HoeffdingTree.Node
filterInstanceToLeaf(Instance, HoeffdingTree.SplitNode, int) - Method in class moa.classifiers.trees.HoeffdingTree.SplitNode
filterInstanceToLeaves(Instance, HoeffdingTree.SplitNode, int, List<HoeffdingTree.FoundNode>, boolean) - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaLearningNode
filterInstanceToLeaves(Instance, HoeffdingTree.SplitNode, int, List<HoeffdingTree.FoundNode>, boolean) - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaSplitNode
filterInstanceToLeaves(Instance, HoeffdingTree.SplitNode, int, boolean) - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree
filterInstanceToLeaves(Instance, HoeffdingTree.SplitNode, int, List<HoeffdingTree.FoundNode>, boolean) - Method in interface moa.classifiers.trees.HoeffdingAdaptiveTree.NewNode
filterInstanceToLeaves(Instance, HoeffdingOptionTree.SplitNode, int, boolean) - Method in class moa.classifiers.trees.HoeffdingOptionTree.Node
filterInstanceToLeaves(Instance, HoeffdingOptionTree.SplitNode, int, List<HoeffdingOptionTree.FoundNode>, boolean) - Method in class moa.classifiers.trees.HoeffdingOptionTree.Node
filterInstanceToLeaves(Instance, HoeffdingOptionTree.SplitNode, int, List<HoeffdingOptionTree.FoundNode>, boolean) - Method in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
filtersOption - Variable in class moa.streams.FilteredStream
filtersOption - Variable in class moa.streams.MultiFilteredStream
FIMTDD - Class in moa.classifiers.trees
FIMTDD() - Constructor for class moa.classifiers.trees.FIMTDD
FIMTDD.FIMTDDPerceptron - Class in moa.classifiers.trees
FIMTDD.FIMTDDPerceptron(FIMTDD.FIMTDDPerceptron) - Constructor for class moa.classifiers.trees.FIMTDD.FIMTDDPerceptron
FIMTDD.FIMTDDPerceptron() - Constructor for class moa.classifiers.trees.FIMTDD.FIMTDDPerceptron
FIMTDD.LeafNode - Class in moa.classifiers.trees
FIMTDD.LeafNode(FIMTDD) - Constructor for class moa.classifiers.trees.FIMTDD.LeafNode: Create a new LeafNode
FIMTDD.Node - Class in moa.classifiers.trees
FIMTDD.Node() - Constructor for class moa.classifiers.trees.FIMTDD.Node
FIMTDD.SplitNode - Class in moa.classifiers.trees
FIMTDD.SplitNode(InstanceConditionalTest, FIMTDD) - Constructor for class moa.classifiers.trees.FIMTDD.SplitNode: Create a new SplitNode
FIMTDDNumericAttributeClassLimitObserver - Class in moa.classifiers.rules.core.attributeclassobservers
FIMTDDNumericAttributeClassLimitObserver() - Constructor for class moa.classifiers.rules.core.attributeclassobservers.FIMTDDNumericAttributeClassLimitObserver
FIMTDDNumericAttributeClassLimitObserver.Node - Class in moa.classifiers.rules.core.attributeclassobservers
FIMTDDNumericAttributeClassLimitObserver.Node(double, double, double) - Constructor for class moa.classifiers.rules.core.attributeclassobservers.FIMTDDNumericAttributeClassLimitObserver.Node
FIMTDDNumericAttributeClassObserver - Class in moa.classifiers.core.attributeclassobservers
FIMTDDNumericAttributeClassObserver() - Constructor for class moa.classifiers.core.attributeclassobservers.FIMTDDNumericAttributeClassObserver
FIMTDDNumericAttributeClassObserver.Node - Class in moa.classifiers.core.attributeclassobservers
FIMTDDNumericAttributeClassObserver.Node(double, double, double) - Constructor for class moa.classifiers.core.attributeclassobservers.FIMTDDNumericAttributeClassObserver.Node
finalResult - Variable in class moa.tasks.TaskThread
findBestSplit(SplitCriterion) - Method in class moa.classifiers.trees.DecisionStump
findBestValEntropy(BinaryTreeNumericAttributeClassObserver.Node, DoubleVector, DoubleVector, boolean, double, DoubleVector) - Method in class moa.classifiers.rules.RuleClassifier
findBestValEntropyNominalAtt(AutoExpandVector<DoubleVector>, int) - Method in class moa.classifiers.rules.RuleClassifier
findClassesInDirectoryRecursive(File, String) - Static method in class moa.core.AutoClassDiscovery
findClassesOfType(String, Class<?>) - Static method in class moa.core.AutoClassDiscovery
findClassNames(String) - Static method in class moa.core.AutoClassDiscovery
findIndexOfTupleGreaterThan(double) - Method in class moa.core.GreenwaldKhannaQuantileSummary
findLearningNodes() - Method in class moa.classifiers.trees.HoeffdingOptionTree
findLearningNodes(HoeffdingOptionTree.Node, HoeffdingOptionTree.SplitNode, int, List<HoeffdingOptionTree.FoundNode>) - Method in class moa.classifiers.trees.HoeffdingOptionTree
findLearningNodes() - Method in class moa.classifiers.trees.HoeffdingTree
findLearningNodes(HoeffdingTree.Node, HoeffdingTree.SplitNode, int, List<HoeffdingTree.FoundNode>) - Method in class moa.classifiers.trees.HoeffdingTree
findMaxDelta() - Method in class moa.core.GreenwaldKhannaQuantileSummary
FindMin() - Method in class moa.clusterers.outliers.MCOD.MCODBase.EventQueue
FindMin() - Method in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase.EventQueue
findNearestNeighbours(Instance, KDTreeNode, int, NearestNeighbourSearch.MyHeap, double) - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Returns (in the supplied heap object) the k nearest neighbours of the given instance starting from the give tree node.
findSuitableClasses(Class<?>) - Method in class moa.gui.ClassOptionSelectionPanel
findSuitableClasses(Class<?>, String[]) - Method in class moa.gui.ClassOptionWithNamesSelectionPanel
findWorstOption() - Method in class moa.classifiers.trees.ORTO
fireClusterChange(long, String, String) - Method in class moa.streams.clustering.RandomRBFGeneratorEvents: Fire a ClusterChangeEvent to all registered listeners
firePropertyChange(String, Object, Object) - Method in class moa.gui.conceptdrift.CDTaskManagerPanel.ProgressCellRenderer
firePropertyChange(String, boolean, boolean) - Method in class moa.gui.conceptdrift.CDTaskManagerPanel.ProgressCellRenderer
firePropertyChange(String, Object, Object) - Method in class moa.gui.RegressionTaskManagerPanel.ProgressCellRenderer
firePropertyChange(String, boolean, boolean) - Method in class moa.gui.RegressionTaskManagerPanel.ProgressCellRenderer
firePropertyChange(String, Object, Object) - Method in class moa.gui.TaskManagerPanel.ProgressCellRenderer
firePropertyChange(String, boolean, boolean) - Method in class moa.gui.TaskManagerPanel.ProgressCellRenderer
fireTaskCompleted() - Method in class moa.tasks.TaskThread
first - Variable in class moa.clusterers.outliers.utils.mtree.utils.Pair: The first object.
FIRST_OBJ_ID - Static variable in class moa.clusterers.outliers.AbstractC.AbstractCBase
FIRST_OBJ_ID - Static variable in class moa.clusterers.outliers.Angiulli.STORMBase
FIRST_OBJ_ID - Static variable in class moa.clusterers.outliers.MCOD.MCODBase
FIRST_OBJ_ID - Static variable in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
firstClassifierSizeOption - Variable in class moa.classifiers.meta.OzaBagASHT
firstHit(Instance) - Method in class moa.classifiers.rules.RuleClassifier
firstHitNB(Instance) - Method in class moa.classifiers.rules.RuleClassifierNBayes
firstLeafLevelOption - Variable in class moa.streams.generators.RandomTreeGenerator
firstValueOption - Variable in class moa.tasks.RunStreamTasks
firstValueOption - Variable in class moa.tasks.RunTasks
FIXED_PANEL_WIDTH - Static variable in class moa.gui.OptionsConfigurationPanel
fixedThresholdOption - Variable in class moa.classifiers.active.ActiveClassifier
FlagOption - Class in moa.options: Flag option.
FlagOption(String, char, String) - Constructor for class moa.options.FlagOption
FlagOptionEditComponent - Class in moa.gui: An OptionEditComponent that lets the user edit a flag option.
FlagOptionEditComponent(FlagOption) - Constructor for class moa.gui.FlagOptionEditComponent
FlixsterDataset - Class in moa.recommender.dataset.impl
FlixsterDataset() - Constructor for class moa.recommender.dataset.impl.FlixsterDataset
FloatOption - Class in moa.options: Float option.
FloatOption(String, char, String, double) - Constructor for class moa.options.FloatOption
FloatOption(String, char, String, double, double, double) - Constructor for class moa.options.FloatOption
FloatOptionEditComponent - Class in moa.gui: An OptionEditComponent that lets the user edit a float option.
FloatOptionEditComponent(FloatOption) - Constructor for class moa.gui.FloatOptionEditComponent
floatValueToSliderValue(double) - Method in class moa.gui.FloatOptionEditComponent
forceAddEvents() - Method in class moa.gui.visualization.GraphCanvas
formatInstance(Instance) - Method in class moa.core.utils.Converter
fract_before - Variable in class moa.clusterers.outliers.Angiulli.ApproxSTORM.ISBNodeAppr
frequencies - Variable in class moa.streams.filters.ReplacingMissingValuesFilter
fromCommandLine(ClassOption, String) - Static method in class weka.core.MOAUtils: Turns a commandline into an object (classname + optional options).
fromCommandLine(Class, String) - Static method in class weka.core.MOAUtils: Turns a commandline into an object (classname + optional options).
fromOption(ClassOption) - Static method in class weka.core.MOAUtils: Creates a MOA object from the specified class option.
fullSizeOf(Object) - Static method in class moa.core.SizeOf: Returns the full size of the object.
functionOption - Variable in class moa.streams.generators.AgrawalGenerator
functionOption - Variable in class moa.streams.generators.SEAGenerator
functionOption - Variable in class moa.streams.generators.STAGGERGenerator

G

g - Variable in class moa.core.GreenwaldKhannaQuantileSummary.Tuple
gamma - Variable in class moa.classifiers.meta.OnlineSmoothBoost
gammaOption - Variable in class moa.classifiers.meta.OnlineSmoothBoost
gammaOption - Variable in class moa.classifiers.meta.WeightedMajorityAlgorithm
GaussianEstimator - Class in moa.core: Gaussian incremental estimator that uses incremental method that is more resistant to floating point imprecision.
GaussianEstimator() - Constructor for class moa.core.GaussianEstimator
gaussianMeans(Clustering, Clustering) - Static method in class moa.clusterers.KMeans
GaussianNumericAttributeClassObserver - Class in moa.classifiers.core.attributeclassobservers: Class for observing the class data distribution for a numeric attribute using gaussian estimators.
GaussianNumericAttributeClassObserver() - Constructor for class moa.classifiers.core.attributeclassobservers.GaussianNumericAttributeClassObserver
General - Class in moa.evaluation
General() - Constructor for class moa.evaluation.General
generateCentroids() - Method in class moa.streams.generators.RandomRBFGenerator
generateCentroids() - Method in class moa.streams.generators.RandomRBFGeneratorDrift
generateConditional(double[], boolean[][]) - Method in class moa.streams.generators.multilabel.MetaMultilabelGenerator: GenerateConditional.
generateExample() - Method in class weka.datagenerators.classifiers.classification.MOA: Generates one example of the dataset.
generateExamples() - Method in class weka.datagenerators.classifiers.classification.MOA: Generates all examples of the dataset.
generateFinished() - Method in class weka.datagenerators.classifiers.classification.MOA: Generates a comment string that documentats the data generator.
generateHeader() - Method in class moa.streams.clustering.RandomRBFGeneratorEvents
generateHeader() - Method in class moa.streams.generators.HyperplaneGenerator
generateHeader() - Method in class moa.streams.generators.RandomRBFGenerator
generateHeader() - Method in class moa.streams.generators.RandomTreeGenerator
generateMultilabelHeader(Instances) - Method in class moa.streams.generators.multilabel.MetaMultilabelGenerator: GenerateMultilabelHeader.
generateRandomTree() - Method in class moa.streams.generators.RandomTreeGenerator
generateRandomTreeNode(int, ArrayList<Integer>, double[], double[], Random) - Method in class moa.streams.generators.RandomTreeGenerator
generateSizeOption - Variable in class moa.tasks.MeasureStreamSpeed
generateStart() - Method in class weka.datagenerators.classifiers.classification.MOA: Generates a comment string that documentates the data generator.
generatorTipText() - Method in class weka.datagenerators.classifiers.classification.MOA: Returns the tooltip displayed in the GUI.
GeometricMovingAverageDM - Class in moa.classifiers.core.driftdetection: Drift detection method based in Geometric Moving Average Test
GeometricMovingAverageDM() - Constructor for class moa.classifiers.core.driftdetection.GeometricMovingAverageDM
get() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.MyHeap: returns the first element and removes it from the heap.
get(int) - Method in class moa.cluster.Clustering: remove a cluster from the clustering
get(int) - Method in class moa.clusterers.outliers.AbstractC.StreamObj
get(int) - Method in class moa.clusterers.outliers.Angiulli.StreamObj
get(int) - Method in class moa.clusterers.outliers.MCOD.MicroCluster
get(int) - Method in class moa.clusterers.outliers.MCOD.StreamObj
get(int) - Method in class moa.clusterers.outliers.SimpleCOD.StreamObj
get(int) - Method in interface moa.clusterers.outliers.utils.mtree.DistanceFunctions.EuclideanCoordinate: A method to access the index-th component of the coordinate.
get(int) - Method in class moa.clusterers.outliers.utils.mtree.utils.Pair: Accesses an object by its index.
get(int) - Method in class moa.core.AutoExpandVector
get(String, String) - Static method in class moa.gui.GUIDefaults: returns the value for the specified property, if non-existent then the default value.
get(int) - Method in class moa.recommender.rc.utils.DenseVector
get(int) - Method in class moa.recommender.rc.utils.SparseVector
get(int) - Method in class moa.recommender.rc.utils.Vector
Get_nn_before() - Method in class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
Get_nn_before() - Method in class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBNode
getActiveXDim() - Method in class moa.gui.visualization.StreamOutlierPanel
getActiveXDim() - Method in class moa.gui.visualization.StreamPanel
getActiveYDim() - Method in class moa.gui.visualization.StreamOutlierPanel
getActiveYDim() - Method in class moa.gui.visualization.StreamPanel
getAcuity() - Method in class moa.clusterers.CobWeb: get the acuity value
getAlgorithm0ValueAsCLIString() - Method in class moa.gui.clustertab.ClusteringAlgoPanel
getAlgorithm0ValueAsCLIString() - Method in class moa.gui.outliertab.OutlierAlgoPanel
getAlgorithm1ValueAsCLIString() - Method in class moa.gui.clustertab.ClusteringAlgoPanel
getAlgorithm1ValueAsCLIString() - Method in class moa.gui.outliertab.OutlierAlgoPanel
getAllValues(int) - Method in class moa.evaluation.MeasureCollection
getAlternateTree() - Method in class moa.classifiers.trees.ORTO.InnerNode
getAMRules() - Method in class moa.classifiers.rules.core.Rule.Builder
getArrayCopy() - Method in class moa.core.DoubleVector
getArrayRef() - Method in class moa.core.DoubleVector
getAsCLIString() - Method in class moa.options.Options
getAttributeIndices() - Method in interface moa.classifiers.lazy.neighboursearch.DistanceFunction: Gets the range of attributes used in the calculation of the distance.
getAttributeIndices() - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Gets the range of attributes used in the calculation of the distance.
getAttributeNameString(int) - Method in class moa.classifiers.AbstractClassifier: Gets the name of an attribute from the header.
getAttributeNameString(int) - Method in class moa.clusterers.AbstractClusterer
getAttributeNameString(InstancesHeader, int) - Static method in class moa.core.InstancesHeader
getAttributeObservers() - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
getAttributeValue() - Method in class moa.classifiers.rules.Predicates
getAttsTestDependsOn() - Method in class moa.classifiers.core.conditionaltests.InstanceConditionalTest: Returns an array with the attributes that the test depends on.
getAttsTestDependsOn() - Method in class moa.classifiers.core.conditionaltests.NominalAttributeBinaryTest
getAttsTestDependsOn() - Method in class moa.classifiers.core.conditionaltests.NominalAttributeMultiwayTest
getAttsTestDependsOn() - Method in class moa.classifiers.core.conditionaltests.NumericAttributeBinaryTest
getAttsTestDependsOn() - Method in class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
getAvgRatingItem(int) - Method in class moa.recommender.rc.data.impl.MemRecommenderData
getAvgRatingItem(int) - Method in interface moa.recommender.rc.data.RecommenderData
getAvgRatingUser(int) - Method in class moa.recommender.rc.data.impl.MemRecommenderData
getAvgRatingUser(int) - Method in interface moa.recommender.rc.data.RecommenderData
getAWTRenderer() - Method in class moa.classifiers.AbstractClassifier: Returns the AWT Renderer
getAWTRenderer() - Method in class moa.clusterers.AbstractClusterer
getAWTRenderer() - Method in interface moa.gui.AWTRenderable
getBestEvaluatedSplitSuggestion(SplitCriterion, double[], int, boolean) - Method in interface moa.classifiers.core.attributeclassobservers.AttributeClassObserver: Gets the best split suggestion given a criterion and a class distribution
getBestEvaluatedSplitSuggestion(SplitCriterion, double[], int, boolean) - Method in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserver
getBestEvaluatedSplitSuggestion(SplitCriterion, double[], int, boolean) - Method in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserverRegression
getBestEvaluatedSplitSuggestion(SplitCriterion, double[], int, boolean) - Method in class moa.classifiers.core.attributeclassobservers.FIMTDDNumericAttributeClassObserver
getBestEvaluatedSplitSuggestion(SplitCriterion, double[], int, boolean) - Method in class moa.classifiers.core.attributeclassobservers.GaussianNumericAttributeClassObserver
getBestEvaluatedSplitSuggestion(SplitCriterion, double[], int, boolean) - Method in class moa.classifiers.core.attributeclassobservers.GreenwaldKhannaNumericAttributeClassObserver
getBestEvaluatedSplitSuggestion(SplitCriterion, double[], int, boolean) - Method in class moa.classifiers.core.attributeclassobservers.NominalAttributeClassObserver
getBestEvaluatedSplitSuggestion(SplitCriterion, double[], int, boolean) - Method in class moa.classifiers.core.attributeclassobservers.NullAttributeClassObserver
getBestEvaluatedSplitSuggestion(SplitCriterion, double[], int, boolean) - Method in class moa.classifiers.core.attributeclassobservers.VFMLNumericAttributeClassObserver
getBestSecondBestEntropy(DoubleVector) - Method in class moa.classifiers.rules.RuleClassifier
getBestSplitSuggestions(SplitCriterion) - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
getBestSplitSuggestions(SplitCriterion, FIMTDD) - Method in class moa.classifiers.trees.FIMTDD.LeafNode: Return the best split suggestions for this node using the given split criteria
getBestSplitSuggestions(SplitCriterion, HoeffdingOptionTree) - Method in class moa.classifiers.trees.HoeffdingOptionTree.ActiveLearningNode
getBestSplitSuggestions(SplitCriterion, HoeffdingTree) - Method in class moa.classifiers.trees.HoeffdingTree.ActiveLearningNode
getBestSplitSuggestions(SplitCriterion, ORTO) - Method in class moa.classifiers.trees.ORTO.ActiveLearningNode: Return the best split suggestions for this node using the given split criteria
getBestSuggestion() - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
getBucketsUsed() - Method in class moa.classifiers.core.driftdetection.ADWIN
getBuffer() - Method in class moa.clusterers.clustree.Entry: Getter for the buffer.
getBuilder() - Method in class moa.classifiers.rules.core.Rule
getBytesRead() - Method in class moa.core.InputStreamProgressMonitor
getBytesRemaining() - Method in class moa.core.InputStreamProgressMonitor
getCapabilities() - Method in class weka.classifiers.meta.MOA: Returns the Capabilities of this classifier.
getCenter() - Method in class moa.cluster.CFCluster
getCenter() - Method in class moa.cluster.Cluster
getCenter() - Method in class moa.cluster.SphereCluster
getCenter() - Method in class moa.clusterers.clustream.ClustreamKernel
getCenter() - Method in class moa.clusterers.clustree.ClusKernel
getCenter() - Method in class moa.clusterers.denstream.MicroCluster
getCenterDistance(Instance) - Method in class moa.cluster.SphereCluster
getCenterDistance(SphereCluster) - Method in class moa.cluster.SphereCluster
getCF() - Method in class moa.cluster.CFCluster
getCF() - Method in class moa.clusterers.clustream.ClustreamKernel
getCF() - Method in class moa.clusterers.clustree.ClusKernel
getCF() - Method in class moa.clusterers.denstream.MicroCluster
getCF() - Method in class moa.clusterers.macro.NonConvexCluster
getCFCluster() - Method in class moa.clusterers.macro.dbscan.DenseMicroCluster
getChange() - Method in class moa.classifiers.core.driftdetection.AbstractChangeDetector: Gets whether there is change detected.
getChange() - Method in class moa.classifiers.core.driftdetection.ADWIN
getChange() - Method in interface moa.classifiers.core.driftdetection.ChangeDetector: Gets whether there is change detected.
getChange() - Method in class moa.streams.generators.cd.AbstractConceptDriftGenerator
getChild(int) - Method in class moa.classifiers.trees.FIMTDD.SplitNode
getChild(int) - Method in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
getChild(int) - Method in class moa.classifiers.trees.HoeffdingTree.SplitNode
getChild(int) - Method in class moa.classifiers.trees.ORTO.InnerNode
getChild() - Method in class moa.clusterers.clustree.Entry: Return the reference to the child of this Entry to navigate in the tree.
getChildIndex(FIMTDD.Node) - Method in class moa.classifiers.trees.FIMTDD.SplitNode
getChildIndex(ORTO.Node) - Method in class moa.classifiers.trees.ORTO.InnerNode
getChildIndex(ORTO.Node) - Method in class moa.classifiers.trees.ORTO.Node
getChosenIndex() - Method in class moa.options.MultiChoiceOption
getChosenLabel() - Method in class moa.options.MultiChoiceOption
getChosenObjectCLIString(Class<?>) - Method in class moa.gui.ClassOptionSelectionPanel
getChosenObjectCLIString(Class<?>) - Method in class moa.gui.ClassOptionWithNamesSelectionPanel
getClassDistribution(int) - Method in class moa.evaluation.MembershipMatrix
getClassDistributionByLabel(int) - Method in class moa.evaluation.MembershipMatrix
getClassDistsResultingFromBinarySplit(double) - Method in class moa.classifiers.core.attributeclassobservers.GaussianNumericAttributeClassObserver
getClassDistsResultingFromBinarySplit(double) - Method in class moa.classifiers.core.attributeclassobservers.GreenwaldKhannaNumericAttributeClassObserver
getClassDistsResultingFromBinarySplit(int) - Method in class moa.classifiers.core.attributeclassobservers.NominalAttributeClassObserver
getClassDistsResultingFromMultiwaySplit(int) - Method in class moa.classifiers.core.attributeclassobservers.NominalAttributeClassObserver
getClassifier() - Method in class moa.classifiers.multilabel.HoeffdingTreeClassifLeaves.LearningNodeClassifier
getClassifier() - Method in class moa.classifiers.multilabel.MultilabelHoeffdingTree.MultilabelLearningNodeClassifier
getClassifier() - Method in class weka.classifiers.meta.MOA: Returns the current MOA classifier in use.
getClassLabel() - Method in class moa.clusterers.outliers.AnyOut.util.DataObject: Return the label for the DataObject.
getClassLabelString(int) - Method in class moa.classifiers.AbstractClassifier: Gets the name of a label of the class from the header.
getClassLabelString(int) - Method in class moa.clusterers.AbstractClusterer
getClassLabelString(InstancesHeader, int) - Static method in class moa.core.InstancesHeader
getClassNames() - Method in class moa.options.ClassOptionWithNames
getClassNameString() - Method in class moa.classifiers.AbstractClassifier: Gets the name of the attribute of the class from the header.
getClassNameString() - Method in class moa.clusterers.AbstractClusterer
getClassNameString(InstancesHeader) - Static method in class moa.core.InstancesHeader
getClassSeparability() - Method in class moa.evaluation.CMM_GTAnalysis: Calculates how well the original clusters are separable.
getClassSum(int) - Method in class moa.evaluation.MembershipMatrix
getClassSumByLabel(int) - Method in class moa.evaluation.MembershipMatrix
getClassVotes(Instance, HoeffdingTree) - Method in class moa.classifiers.multilabel.HoeffdingTreeClassifLeaves.LearningNodeClassifier
getClassVotes(Instance, HoeffdingTree) - Method in class moa.classifiers.multilabel.MultilabelHoeffdingTree.MultilabelLearningNodeClassifier
getClassVotes(Instance, HoeffdingOptionTree) - Method in class moa.classifiers.trees.AdaHoeffdingOptionTree.AdaLearningNode
getClassVotes(Instance, FIMTDD) - Method in class moa.classifiers.trees.FIMTDD.LeafNode
getClassVotes(Instance, HoeffdingTree) - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaLearningNode
getClassVotes(Instance, HoeffdingOptionTree) - Method in class moa.classifiers.trees.HoeffdingOptionTree.LearningNodeNB
getClassVotes(Instance, HoeffdingOptionTree) - Method in class moa.classifiers.trees.HoeffdingOptionTree.LearningNodeNBAdaptive
getClassVotes(Instance, HoeffdingOptionTree) - Method in class moa.classifiers.trees.HoeffdingOptionTree.Node
getClassVotes(Instance, HoeffdingTree) - Method in class moa.classifiers.trees.HoeffdingTree.LearningNodeNB
getClassVotes(Instance, HoeffdingTree) - Method in class moa.classifiers.trees.HoeffdingTree.LearningNodeNBAdaptive
getClassVotes(Instance, HoeffdingTree) - Method in class moa.classifiers.trees.HoeffdingTree.Node
getClassVotes(Instance, HoeffdingTree) - Method in class moa.classifiers.trees.LimAttHoeffdingTree.LearningNodeNB
getClassVotes(Instance, HoeffdingTree) - Method in class moa.classifiers.trees.LimAttHoeffdingTree.LearningNodeNBAdaptive
getClassVotes(Instance, HoeffdingTree) - Method in class moa.classifiers.trees.RandomHoeffdingTree.LearningNodeNB
getClassVotes(Instance, HoeffdingTree) - Method in class moa.classifiers.trees.RandomHoeffdingTree.LearningNodeNBAdaptive
getCLIChar() - Method in class moa.options.AbstractOption
getCLIChar() - Method in interface moa.options.Option: Gets the Command Line Interface text of this option
getCLICreationString(Class<?>) - Method in class moa.options.AbstractOptionHandler
getCLICreationString(Class<?>) - Method in interface moa.options.OptionHandler: Gets the Command Line Interface text to create the object
getClock() - Method in class moa.classifiers.core.driftdetection.ADWIN
getClusterClassWeight(int, int) - Method in class moa.evaluation.MembershipMatrix
getClusterClassWeightByLabel(int, int) - Method in class moa.evaluation.MembershipMatrix
getClusterer0() - Method in class moa.gui.clustertab.ClusteringAlgoPanel
getClusterer0() - Method in class moa.gui.clustertab.ClusteringSetupTab
getClusterer0() - Method in class moa.gui.outliertab.OutlierAlgoPanel
getClusterer1() - Method in class moa.gui.clustertab.ClusteringAlgoPanel
getClusterer1() - Method in class moa.gui.clustertab.ClusteringSetupTab
getClusterer1() - Method in class moa.gui.outliertab.OutlierAlgoPanel
getClusterID() - Method in class moa.gui.visualization.ClusterPanel
getClusterID() - Method in class moa.gui.visualization.OutlierPanel
getClustering() - Method in class moa.cluster.Clustering
getClustering(long, int) - Method in class moa.clusterers.clustree.ClusTree
getClustering(Clustering) - Method in class moa.clusterers.macro.AbstractMacroClusterer
getClustering(Clustering) - Method in class moa.clusterers.macro.dbscan.DBScan
getClustering() - Method in interface moa.clusterers.macro.IDenseMacroCluster
getClustering(Clustering) - Method in interface moa.clusterers.macro.IMacroClusterer
getClustering() - Method in class moa.clusterers.macro.NonConvexCluster
getClusteringCopy() - Method in class moa.cluster.Clustering
getClusteringResult() - Method in interface moa.clusterers.Clusterer
getClusteringResult() - Method in class moa.clusterers.ClusterGenerator
getClusteringResult() - Method in class moa.clusterers.clustream.Clustream
getClusteringResult() - Method in class moa.clusterers.clustream.WithKmeans
getClusteringResult(Clustering) - Method in class moa.clusterers.clustream.WithKmeans
getClusteringResult() - Method in class moa.clusterers.clustree.ClusTree
getClusteringResult() - Method in class moa.clusterers.CobWeb
getClusteringResult() - Method in class moa.clusterers.denstream.WithDBSCAN
getClusteringResult() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
getClusteringResult() - Method in class moa.clusterers.streamkm.StreamKM
getClusteringResult() - Method in class moa.clusterers.WekaClusteringAlgorithm
getClusterLabel() - Method in class moa.gui.visualization.ClusterPanel
getClusterLabel() - Method in class moa.gui.visualization.OutlierPanel
getClusterSpecificInfo(ArrayList<String>, ArrayList<String>) - Method in class moa.cluster.Cluster
getClusterSpecificInfo(ArrayList<String>, ArrayList<String>) - Method in class moa.cluster.SphereCluster
getClusterSpecificInfo(ArrayList<String>, ArrayList<String>) - Method in class moa.clusterers.clustream.ClustreamKernel
getClusterSum(int) - Method in class moa.evaluation.MembershipMatrix
getColor(int) - Static method in class moa.clusterers.macro.ColorArray
getColor() - Method in class moa.clusterers.macro.ColorObject
getColumnCount() - Method in class moa.gui.conceptdrift.CDTaskManagerPanel.TaskTableModel
getColumnCount() - Method in class moa.gui.LineGraphViewPanel.PlotTableModel
getColumnCount() - Method in class moa.gui.RegressionTaskManagerPanel.TaskTableModel
getColumnCount() - Method in class moa.gui.TaskManagerPanel.TaskTableModel
getColumnName(int) - Method in class moa.gui.conceptdrift.CDTaskManagerPanel.TaskTableModel
getColumnName(int) - Method in class moa.gui.LineGraphViewPanel.PlotTableModel
getColumnName(int) - Method in class moa.gui.RegressionTaskManagerPanel.TaskTableModel
getColumnName(int) - Method in class moa.gui.TaskManagerPanel.TaskTableModel
getConfidence(int) - Method in class moa.clusterers.outliers.AnyOut.AnyOutCore
getConnectionValue(CMM_GTAnalysis.CMMPoint, int) - Method in class moa.evaluation.CMM_GTAnalysis: Calculate the connection of a point to a cluster
getCountBelow(double) - Method in class moa.core.GreenwaldKhannaQuantileSummary
getCountNominalAttrib(ArrayList<Predicates>) - Method in class moa.classifiers.rules.RuleClassifier
getCPUSecondsElapsed() - Method in class moa.tasks.TaskThread
getCreationTime() - Method in class moa.clusterers.denstream.MicroCluster
getCumulativeSum() - Method in class moa.classifiers.rules.driftdetection.PageHinkleyTest
getCurrentActivityDescription() - Method in class moa.tasks.NullMonitor
getCurrentActivityDescription() - Method in class moa.tasks.StandardTaskMonitor
getCurrentActivityDescription() - Method in interface moa.tasks.TaskMonitor: Gets the description of the current activity.
getCurrentActivityFracComplete() - Method in class moa.tasks.TaskThread
getCurrentActivityFractionComplete() - Method in class moa.tasks.NullMonitor
getCurrentActivityFractionComplete() - Method in class moa.tasks.StandardTaskMonitor
getCurrentActivityFractionComplete() - Method in interface moa.tasks.TaskMonitor: Gets the percentage done of the current activity
getCurrentActivityString() - Method in class moa.tasks.TaskThread
getCurrenTask() - Method in class moa.gui.conceptdrift.CDTaskManagerPanel
getCurrentError() - Method in class moa.classifiers.rules.core.Rule
getCurrentError() - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
getCurrentError() - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
getCurrentError() - Method in class moa.classifiers.rules.functions.Perceptron
getCurrentError() - Method in class moa.classifiers.rules.functions.TargetMean
getCurrentStatusString() - Method in class moa.tasks.TaskThread
getCurrentTimestamp() - Static method in class moa.gui.visualization.RunOutlierVisualizer
getCurrentTimestamp() - Static method in class moa.gui.visualization.RunVisualizer
getCustomEditor() - Method in class weka.gui.MOAClassOptionEditor: Gets the custom editor component.
getCutoff() - Method in class moa.clusterers.CobWeb: get the cutoff
getData() - Method in class moa.clusterers.clustree.Entry: Getter for the data.
getData() - Method in class moa.recommender.data.MemRecommenderData
getData() - Method in interface moa.recommender.data.RecommenderData
getData() - Method in class moa.recommender.predictor.BaselinePredictor
getData() - Method in class moa.recommender.predictor.BRISMFPredictor
getData() - Method in interface moa.recommender.predictor.RatingPredictor
getData() - Method in class moa.recommender.rc.predictor.impl.BaselinePredictor
getData() - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
getData() - Method in interface moa.recommender.rc.predictor.RatingPredictor
getDataObjectArray() - Method in class moa.clusterers.outliers.AnyOut.util.DataSet: Returns an array of all the DataObjects in the set.
getDataset(int, int) - Method in class moa.clusterers.WekaClusteringAlgorithm
getDataSetsPerClass() - Method in class moa.clusterers.outliers.AnyOut.util.DataSet: Separates the objects in this data set according to their class label
getDecayHorizon() - Method in class moa.streams.clustering.ClusteringStream
getDecayThreshold() - Method in class moa.streams.clustering.ClusteringStream
getDefaultCLIString() - Method in class moa.options.AbstractClassOption
getDefaultCLIString() - Method in class moa.options.FlagOption
getDefaultCLIString() - Method in class moa.options.FloatOption
getDefaultCLIString() - Method in class moa.options.IntOption
getDefaultCLIString() - Method in class moa.options.ListOption
getDefaultCLIString() - Method in class moa.options.MultiChoiceOption
getDefaultCLIString() - Method in interface moa.options.Option: Gets the Command Line Interface text
getDefaultCLIString() - Method in class moa.options.StringOption
getDefaultEnabled() - Method in class moa.evaluation.Accuracy
getDefaultEnabled() - Method in class moa.evaluation.ChangeDetectionMeasures
getDefaultEnabled() - Method in class moa.evaluation.CMM
getDefaultEnabled() - Method in class moa.evaluation.EntropyCollection
getDefaultEnabled() - Method in class moa.evaluation.MeasureCollection
getDefaultEnabled() - Method in class moa.evaluation.OutlierPerformance
getDefaultEnabled() - Method in class moa.evaluation.RegressionAccuracy
getDefaultEnabled() - Method in class moa.evaluation.SilhouetteCoefficient
getDefaultEnabled() - Method in class moa.evaluation.SSQ
getDefaultEnabled() - Method in class moa.evaluation.StatisticalCollection
getDefaultFileExtension() - Method in class moa.options.FileOption
getDefaultHeight() - Method in class moa.clusterers.clustree.ClusTree
getDelay() - Method in class moa.classifiers.core.driftdetection.AbstractChangeDetector: Gets the length of the delay in the change detected.
getDelay() - Method in interface moa.classifiers.core.driftdetection.ChangeDetector: Gets the length of the delay in the change detected.
getDescription(StringBuilder, int) - Method in class moa.classifiers.AbstractClassifier
getDescription(StringBuilder, int) - Method in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserver
getDescription(StringBuilder, int) - Method in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserverRegression
getDescription(StringBuilder, int) - Method in class moa.classifiers.core.attributeclassobservers.FIMTDDNumericAttributeClassObserver
getDescription(StringBuilder, int) - Method in class moa.classifiers.core.attributeclassobservers.GaussianNumericAttributeClassObserver
getDescription(StringBuilder, int) - Method in class moa.classifiers.core.attributeclassobservers.GreenwaldKhannaNumericAttributeClassObserver
getDescription(StringBuilder, int) - Method in class moa.classifiers.core.attributeclassobservers.NominalAttributeClassObserver
getDescription(StringBuilder, int) - Method in class moa.classifiers.core.attributeclassobservers.NullAttributeClassObserver
getDescription(StringBuilder, int) - Method in class moa.classifiers.core.attributeclassobservers.VFMLNumericAttributeClassObserver
getDescription(StringBuilder, int) - Method in class moa.classifiers.core.AttributeSplitSuggestion
getDescription(StringBuilder, int) - Method in class moa.classifiers.core.conditionaltests.NominalAttributeBinaryTest
getDescription(StringBuilder, int) - Method in class moa.classifiers.core.conditionaltests.NominalAttributeMultiwayTest
getDescription(StringBuilder, int) - Method in class moa.classifiers.core.conditionaltests.NumericAttributeBinaryTest
getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.AbstractChangeDetector: Returns a string representation of the model.
getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.ADWIN
getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.ADWINChangeDetector
getDescription(StringBuilder, int) - Method in interface moa.classifiers.core.driftdetection.ChangeDetector: Returns a string representation of the model.
getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.CusumDM
getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.DDM
getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.EDDM
getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.EnsembleDriftDetectionMethods
getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.EWMAChartDM
getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.GeometricMovingAverageDM
getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.HDDM_A_Test
getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.HDDM_W_Test
getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.PageHinkleyDM
getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.SeqDrift1ChangeDetector
getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector
getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.SeqDrift2
getDescription(StringBuilder, int) - Method in class moa.classifiers.core.splitcriteria.GiniSplitCriterion
getDescription(StringBuilder, int) - Method in class moa.classifiers.core.splitcriteria.InfoGainSplitCriterion
getDescription(StringBuilder, int) - Method in class moa.classifiers.core.splitcriteria.VarianceReductionSplitCriterion
getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.core.Rule: MOA GUI output
getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.core.voting.InverseErrorWeightedVote
getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.core.voting.UniformWeightedVote
getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.Predicates
getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.RuleClassification
getDescription(StringBuilder, int) - Method in class moa.classifiers.trees.FIMTDD.Node
getDescription(StringBuilder, int) - Method in class moa.classifiers.trees.HoeffdingOptionTree.Node
getDescription(StringBuilder, int) - Method in class moa.classifiers.trees.HoeffdingTree.Node
getDescription(StringBuilder, int) - Method in class moa.classifiers.trees.ORTO.Node
getDescription(StringBuilder, int) - Method in class moa.classifiers.trees.ORTO.ORTOPerceptron
getDescription(StringBuilder, int) - Method in class moa.cluster.Cluster
getDescription(StringBuilder, int) - Method in class moa.cluster.Clustering
getDescription(StringBuilder, int) - Method in class moa.clusterers.AbstractClusterer
getDescription(StringBuilder, int) - Method in class moa.clusterers.denstream.Timestamp
getDescription(StringBuilder, int) - Method in class moa.core.AutoExpandVector
getDescription(StringBuilder, int) - Method in class moa.core.DoubleVector
getDescription(StringBuilder, int) - Method in class moa.core.GaussianEstimator
getDescription(StringBuilder, int) - Method in class moa.core.GreenwaldKhannaQuantileSummary
getDescription(StringBuilder, int) - Method in class moa.core.Measurement
getDescription(StringBuilder, int) - Method in class moa.core.utils.Converter
getDescription(StringBuilder, int) - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator
getDescription(StringBuilder, int) - Method in class moa.evaluation.BasicClusteringPerformanceEvaluator
getDescription(StringBuilder, int) - Method in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
getDescription(StringBuilder, int) - Method in class moa.evaluation.BasicRegressionPerformanceEvaluator
getDescription(StringBuilder, int) - Method in class moa.evaluation.EWMAClassificationPerformanceEvaluator
getDescription(StringBuilder, int) - Method in class moa.evaluation.FadingFactorClassificationPerformanceEvaluator
getDescription(StringBuilder, int) - Method in class moa.evaluation.LearningCurve
getDescription(StringBuilder, int) - Method in class moa.evaluation.LearningEvaluation
getDescription(StringBuilder, int) - Method in class moa.evaluation.MeasureCollection
getDescription(StringBuilder, int) - Method in class moa.evaluation.MultilabelWindowClassificationPerformanceEvaluator
getDescription(StringBuilder, int) - Method in class moa.evaluation.WindowClassificationPerformanceEvaluator
getDescription(StringBuilder, int) - Method in class moa.evaluation.WindowRegressionPerformanceEvaluator
getDescription() - Method in class moa.gui.AbstractTabPanel: Returns a short description (can be used as tool tip) of the tab, or contributor, etc.
getDescription() - Method in class moa.gui.ClassificationTabPanel
getDescription() - Method in class moa.gui.clustertab.ClusteringTabPanel
getDescription() - Method in class moa.gui.ConceptDriftTabPanel
getDescription() - Method in class moa.gui.FileExtensionFilter
getDescription() - Method in class moa.gui.outliertab.OutlierTabPanel
getDescription() - Method in class moa.gui.RegressionTabPanel
getDescription(StringBuilder, int) - Method in interface moa.MOAObject: Returns a string representation of this object.
getDescription(StringBuilder, int) - Method in class moa.options.AbstractOption
getDescription(StringBuilder, int) - Method in class moa.options.Options
getDescription(StringBuilder, int) - Method in class moa.recommender.data.MemRecommenderData
getDescription(StringBuilder, int) - Method in class moa.recommender.dataset.impl.FlixsterDataset
getDescription(StringBuilder, int) - Method in class moa.recommender.dataset.impl.JesterDataset
getDescription(StringBuilder, int) - Method in class moa.recommender.dataset.impl.MovielensDataset
getDescription(StringBuilder, int) - Method in class moa.recommender.predictor.BaselinePredictor
getDescription(StringBuilder, int) - Method in class moa.recommender.predictor.BRISMFPredictor
getDescription(StringBuilder, int) - Method in class moa.streams.ArffFileStream
getDescription(StringBuilder, int) - Method in class moa.streams.CachedInstancesStream
getDescription(StringBuilder, int) - Method in class moa.streams.clustering.FileStream
getDescription(StringBuilder, int) - Method in class moa.streams.clustering.RandomRBFGeneratorEvents: TOOLS
getDescription(StringBuilder, int) - Method in class moa.streams.ConceptDriftRealStream
getDescription(StringBuilder, int) - Method in class moa.streams.ConceptDriftStream
getDescription(StringBuilder, int) - Method in class moa.streams.FilteredStream
getDescription(StringBuilder, int) - Method in class moa.streams.filters.AddNoiseFilter
getDescription(StringBuilder, int) - Method in class moa.streams.filters.CacheFilter
getDescription(StringBuilder, int) - Method in class moa.streams.filters.ReplacingMissingValuesFilter
getDescription(StringBuilder, int) - Method in class moa.streams.generators.AgrawalGenerator
getDescription(StringBuilder, int) - Method in class moa.streams.generators.cd.AbstractConceptDriftGenerator
getDescription(StringBuilder, int) - Method in class moa.streams.generators.HyperplaneGenerator
getDescription(StringBuilder, int) - Method in class moa.streams.generators.LEDGenerator
getDescription(StringBuilder, int) - Method in class moa.streams.generators.LEDGeneratorDrift
getDescription(StringBuilder, int) - Method in class moa.streams.generators.multilabel.MetaMultilabelGenerator
getDescription(StringBuilder, int) - Method in class moa.streams.generators.RandomRBFGenerator
getDescription(StringBuilder, int) - Method in class moa.streams.generators.RandomRBFGeneratorDrift
getDescription(StringBuilder, int) - Method in class moa.streams.generators.RandomTreeGenerator
getDescription(StringBuilder, int) - Method in class moa.streams.generators.SEAGenerator
getDescription(StringBuilder, int) - Method in class moa.streams.generators.STAGGERGenerator
getDescription(StringBuilder, int) - Method in class moa.streams.generators.WaveformGenerator
getDescription(StringBuilder, int) - Method in class moa.streams.generators.WaveformGeneratorDrift
getDescription(StringBuilder, int) - Method in class moa.streams.MultiFilteredStream
getDescription(StringBuilder, int) - Method in class moa.tasks.AbstractTask
getDescription(StringBuilder, int) - Method in class moa.tasks.FailedTaskReport
getDescriptions() - Static method in enum moa.tasks.Plot.LegendLocation: Gets an array of string descriptions - one for each enum value.
getDescriptions() - Static method in enum moa.tasks.Plot.LegendType: Gets an array of string descriptions - one for each enum value.
getDescriptions() - Static method in enum moa.tasks.Plot.PlotStyle: Gets an array of string descriptions = one for each enum value.
getDescriptions() - Static method in enum moa.tasks.Plot.Terminal: Gets an array of string descriptions - one for each enum value.
getDetect() - Method in class moa.classifiers.core.driftdetection.ADWIN
getDistance(DataPoint) - Method in class moa.gui.visualization.DataPoint
getDistanceFunction() - Method in class moa.classifiers.lazy.neighboursearch.KDTree: returns the distance function currently in use.
getDistanceFunction() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch: returns the distance function currently in use.
getDistances() - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Returns the distances to the kNearest or 1 nearest neighbour currently found with either the kNearestNeighbours or the nearestNeighbour method.
getDistances() - Method in class moa.classifiers.lazy.neighboursearch.LinearNNSearch: Returns the distances of the k nearest neighbours.
getDistances() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch: Returns the distances of the k nearest neighbours.
getDistanceVector(Instance) - Method in class moa.cluster.SphereCluster
getDistanceVector(SphereCluster) - Method in class moa.cluster.SphereCluster
getDontNormalize() - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Gets whether if the attribute values are to be normazlied in distance calculation.
getEditComponent() - Method in class moa.options.AbstractClassOption
getEditComponent() - Method in class moa.options.AbstractOption
getEditComponent() - Method in class moa.options.ClassOption
getEditComponent() - Method in class moa.options.ClassOptionWithNames
getEditComponent() - Method in class moa.options.FileOption
getEditComponent() - Method in class moa.options.FlagOption
getEditComponent() - Method in class moa.options.FloatOption
getEditComponent() - Method in class moa.options.IntOption
getEditComponent() - Method in class moa.options.MultiChoiceOption
getEditComponent() - Method in interface moa.options.Option: Gets the GUI component to edit
getEditComponent() - Method in class moa.options.WEKAClassOption
getEditedOption() - Method in class moa.gui.ClassOptionEditComponent
getEditedOption() - Method in class moa.gui.ClassOptionWithNamesEditComponent
getEditedOption() - Method in class moa.gui.FileOptionEditComponent
getEditedOption() - Method in class moa.gui.FlagOptionEditComponent
getEditedOption() - Method in class moa.gui.FloatOptionEditComponent
getEditedOption() - Method in class moa.gui.IntOptionEditComponent
getEditedOption() - Method in class moa.gui.MultiChoiceOptionEditComponent
getEditedOption() - Method in interface moa.gui.OptionEditComponent: Gets the option of this component
getEditedOption() - Method in class moa.gui.StringOptionEditComponent
getEditedOption() - Method in class moa.gui.WEKAClassOptionEditComponent
getEMClusteringVariances(double[][], int) - Method in class moa.clusterers.outliers.AnyOut.util.EMProjectedClustering: Performs an EM clustering on the provided data set !! Only the variances are calculated and used for point assignments ! !!! the number k' of returned clusters might be smaller than k !!!
getEMClusteringVariancesBestChoice(double[][], int, int) - Method in class moa.clusterers.outliers.AnyOut.util.EMProjectedClustering
getEnsembleMemberWeight(int) - Method in class moa.classifiers.meta.OCBoost
getEnsembleMemberWeight(int) - Method in class moa.classifiers.meta.OnlineSmoothBoost
getEnsembleMemberWeight(int) - Method in class moa.classifiers.meta.OzaBoost
getEnsembleMemberWeight(int) - Method in class moa.classifiers.meta.OzaBoostAdwin
getEntries() - Method in class moa.clusterers.clustree.Node: Return an array with references to the children of this node.
getError(Instance) - Method in class moa.classifiers.trees.ORTO.ActiveLearningNode: Return the error for a given instance
getErrorEstimation() - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaLearningNode
getErrorEstimation() - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaSplitNode
getErrorEstimation() - Method in interface moa.classifiers.trees.HoeffdingAdaptiveTree.NewNode
getErrorWidth() - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaLearningNode
getErrorWidth() - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaSplitNode
getErrorWidth() - Method in interface moa.classifiers.trees.HoeffdingAdaptiveTree.NewNode
getEstimation() - Method in class moa.classifiers.core.driftdetection.AbstractChangeDetector: Gets the prediction of next values.
getEstimation() - Method in class moa.classifiers.core.driftdetection.ADWIN
getEstimation() - Method in interface moa.classifiers.core.driftdetection.ChangeDetector: Gets the prediction of next values.
getEstimation() - Method in class moa.classifiers.core.driftdetection.HDDM_A_Test
getEstimation() - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.SeqDrift2: Gets the prediction of next values.
getEstimatorInfo() - Method in class moa.classifiers.core.driftdetection.ADWIN
getEvalPanel() - Method in class moa.gui.clustertab.ClusteringVisualTab
getEvalPanel() - Method in class moa.gui.outliertab.OutlierVisualTab
getEvaluationFrequency() - Method in class moa.streams.clustering.ClusteringStream
getEventsList() - Method in class moa.streams.generators.cd.AbstractConceptDriftGenerator
getEventsList() - Method in interface moa.streams.generators.cd.ConceptDriftGenerator
getEventsList() - Method in class moa.tasks.ConceptDriftMainTask
getEventsList() - Method in class moa.tasks.RegressionMainTask
getEventType(int) - Method in class moa.evaluation.MeasureCollection
getFailureReason() - Method in class moa.tasks.FailedTaskReport
getFeatures() - Method in class moa.clusterers.outliers.AnyOut.util.DataObject: Returns the features (label attribute excluded).
getFeaturesAsArray() - Method in class moa.clusterers.outliers.AnyOut.util.DataSet: Returns an array with all the features of all the objects in the set.
getFFRatio(int) - Method in class moa.classifiers.trees.ORTO.OptionNode
getFile() - Method in class moa.options.FileOption
getFinalResult() - Method in class moa.tasks.TaskThread
getFirst() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborList: returns the first element in the list.
getFirst() - Method in class moa.recommender.rc.utils.Pair
getFractionCorrectlyClassified() - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator
getFractionCorrectlyClassified() - Method in class moa.evaluation.BasicClusteringPerformanceEvaluator
getFractionCorrectlyClassified() - Method in class moa.evaluation.EWMAClassificationPerformanceEvaluator
getFractionCorrectlyClassified() - Method in class moa.evaluation.FadingFactorClassificationPerformanceEvaluator
getFractionCorrectlyClassified() - Method in class moa.evaluation.WindowClassificationPerformanceEvaluator
getFractionIncorrectlyClassified() - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator
getFractionIncorrectlyClassified() - Method in class moa.evaluation.BasicClusteringPerformanceEvaluator
getFractionIncorrectlyClassified() - Method in class moa.evaluation.EWMAClassificationPerformanceEvaluator
getFractionIncorrectlyClassified() - Method in class moa.evaluation.FadingFactorClassificationPerformanceEvaluator
getFractionIncorrectlyClassified() - Method in class moa.evaluation.WindowClassificationPerformanceEvaluator
getGeneratingClusters() - Method in class moa.streams.clustering.RandomRBFGeneratorEvents
getGenerator() - Method in class weka.datagenerators.classifiers.classification.MOA: Returns the current MOA stream generator in use.
getGlobalMean() - Method in class moa.recommender.rc.data.impl.MemRecommenderData
getGlobalMean() - Method in interface moa.recommender.rc.data.RecommenderData
getGraphCanvas() - Method in class moa.gui.clustertab.ClusteringVisualTab
getGraphCanvas() - Method in class moa.gui.outliertab.OutlierVisualTab
getGroundTruth() - Method in class moa.cluster.Cluster
getGT0Cluster(int) - Method in class moa.evaluation.CMM_GTAnalysis: Return cluster
getHalf(boolean) - Method in class moa.classifiers.meta.DACC: Returns the best (or worst) half of classifiers in the adaptive ensemble.
getHeader() - Method in class moa.streams.ArffFileStream
getHeader() - Method in class moa.streams.CachedInstancesStream
getHeader() - Method in class moa.streams.clustering.FileStream
getHeader() - Method in class moa.streams.clustering.RandomRBFGeneratorEvents
getHeader() - Method in class moa.streams.ConceptDriftRealStream
getHeader() - Method in class moa.streams.ConceptDriftStream
getHeader() - Method in class moa.streams.FilteredStream
getHeader() - Method in class moa.streams.filters.AddNoiseFilter
getHeader() - Method in class moa.streams.filters.CacheFilter
getHeader() - Method in class moa.streams.filters.ReplacingMissingValuesFilter
getHeader() - Method in class moa.streams.generators.AgrawalGenerator
getHeader() - Method in class moa.streams.generators.cd.AbstractConceptDriftGenerator
getHeader() - Method in class moa.streams.generators.HyperplaneGenerator
getHeader() - Method in class moa.streams.generators.LEDGenerator
getHeader() - Method in class moa.streams.generators.multilabel.MetaMultilabelGenerator
getHeader() - Method in class moa.streams.generators.multilabel.MultilabelArffFileStream
getHeader() - Method in class moa.streams.generators.RandomRBFGenerator
getHeader() - Method in class moa.streams.generators.RandomTreeGenerator
getHeader() - Method in class moa.streams.generators.SEAGenerator
getHeader() - Method in class moa.streams.generators.STAGGERGenerator
getHeader() - Method in class moa.streams.generators.WaveformGenerator
getHeader() - Method in interface moa.streams.InstanceStream: Gets the header of this stream.
getHeader() - Method in class moa.streams.MultiFilteredStream
getHeadOptionCount() - Method in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
getHeight() - Method in class moa.clusterers.clustree.ClusTree: Return the current height of the tree.
getHelp(StringBuilder, int) - Method in class moa.options.Options
getHelpString() - Method in class moa.options.Options
getHelpText() - Method in class moa.gui.OptionsConfigurationPanel
getHighlightedClusterPanel() - Method in class moa.gui.visualization.StreamPanel
getHighlightedOutlierPanel() - Method in class moa.gui.visualization.StreamOutlierPanel
getHullDistance(SphereCluster) - Method in class moa.cluster.SphereCluster
getId() - Method in class moa.cluster.Cluster
getId() - Method in class moa.clusterers.outliers.AnyOut.util.DataObject: Returns the id for the DataObject.
getIdxs() - Method in class moa.recommender.rc.utils.DenseVector
getIdxs() - Method in class moa.recommender.rc.utils.SparseVector
getIdxs() - Method in class moa.recommender.rc.utils.Vector
getInclusionProbability(Instance) - Method in class moa.cluster.CFCluster
getInclusionProbability(Instance) - Method in class moa.cluster.Cluster: Returns the probability of the given point belonging to this cluster.
getInclusionProbability(Instance) - Method in class moa.cluster.SphereCluster
getInclusionProbability(Instance) - Method in class moa.clusterers.clustream.ClustreamKernel: See interface Cluster
getInclusionProbability(Instance) - Method in class moa.clusterers.clustree.ClusKernel
getInclusionProbability(Instance) - Method in class moa.clusterers.denstream.MicroCluster
getInclusionProbability(Instance) - Method in class moa.clusterers.macro.NonConvexCluster
getInclusionProbability(CMM_GTAnalysis.CMMPoint) - Method in class moa.evaluation.CMM_GTAnalysis.GTCluster: Calculate the probability of the point being covered through the cluster
getInfo() - Method in class moa.cluster.Cluster
getInfo(int, int) - Method in class moa.gui.visualization.DataPoint
getInfo() - Method in class moa.gui.visualization.OutlierPanel
getInitalBuildTimestamp() - Method in class moa.evaluation.MembershipMatrix
getInitialDirectory() - Static method in class moa.gui.GUIDefaults: Returns the initial directory for the file chooser used for opening datasets.
getInputValues() - Method in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
getInstance() - Method in class moa.clusterers.outliers.AnyOut.util.DataObject: Return the Instance of the DataObject.
getInstances() - Method in interface moa.classifiers.lazy.neighboursearch.DistanceFunction: returns the instances currently set.
getInstances() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch: returns the instances currently set.
getInstances() - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: returns the instances currently set.
getInstancesSeen() - Method in class moa.classifiers.rules.core.Rule
getInstancesSeen() - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
getInstancesSeen() - Method in class moa.classifiers.rules.functions.Perceptron
getInstanceValues(Instance) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
GetInterval() - Method in interface moa.clusterers.outliers.MyBaseOutlierDetector.ProgressInfo
getInvertSelection() - Method in interface moa.classifiers.lazy.neighboursearch.DistanceFunction: Gets whether the matching sense of attribute indices is inverted or not.
getInvertSelection() - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Gets whether the matching sense of attribute indices is inverted or not.
getIrrelevantEntry(double) - Method in class moa.clusterers.clustree.Node: If there exists an entry, whose relevance is under the threshold given as a parameter to the tree, this entry is returned.
getItemFeatures(int) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
getItems() - Method in class moa.recommender.rc.data.impl.MemRecommenderData
getItems() - Method in interface moa.recommender.rc.data.RecommenderData
getKappaStatistic() - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator
getKappaStatistic() - Method in class moa.evaluation.WindowClassificationPerformanceEvaluator
getKappaTemporalStatistic() - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator
getKappaTemporalStatistic() - Method in class moa.evaluation.WindowClassificationPerformanceEvaluator
getKthNearest() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.MyHeap: returns the kth nearest element or null if none there.
getL() - Method in class moa.core.utils.Converter
getLabel() - Method in class moa.evaluation.CMM_GTAnalysis.GTCluster: The original class label the cluster represents
getLambda() - Method in class moa.classifiers.functions.SGD: Get the current value of lambda
getLambda() - Method in class moa.classifiers.functions.SGDMultiClass: Get the current value of lambda
getLambda() - Method in class moa.classifiers.functions.SPegasos: Get the current value of lambda
getLast() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborList: returns the last element in the list.
getLastEditTimestamp() - Method in class moa.clusterers.denstream.MicroCluster
getLastValue(int) - Method in class moa.evaluation.MeasureCollection
getLatestPreviewGrabTimeSeconds() - Method in class moa.tasks.TaskThread
getLatestResultPreview() - Method in class moa.tasks.NullMonitor
getLatestResultPreview() - Method in class moa.tasks.StandardTaskMonitor
getLatestResultPreview() - Method in interface moa.tasks.TaskMonitor: Gets the current result to preview
getLatestResultPreview() - Method in class moa.tasks.TaskThread
getLearnerToUse(Instance, int) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
getLearnerToUse(Instance, int) - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
getLearningNode() - Method in class moa.classifiers.rules.core.Rule: getLearningNode Method This is the way to pass info for other classes.
getLearningRate() - Method in class moa.classifiers.functions.SGD: Get the learning rate.
getLearningRate() - Method in class moa.classifiers.functions.SGDMultiClass: Get the learning rate.
getLeftStreamPanel() - Method in class moa.gui.clustertab.ClusteringVisualTab
getLeftStreamPanel() - Method in class moa.gui.outliertab.OutlierVisualTab
getLevel() - Method in class moa.classifiers.trees.ORTO.Node
getLevel(ClusTree) - Method in class moa.clusterers.clustree.Node: Returns the level at which this node is in the tree.
getList() - Method in class moa.options.ListOption
getLogPanel() - Method in class moa.gui.clustertab.ClusteringSetupTab
getLogPanel() - Method in class moa.gui.outliertab.OutlierSetupTab
getLossFunction() - Method in class moa.classifiers.functions.SGD: Get the current loss function.
getLossFunction() - Method in class moa.classifiers.functions.SGDMultiClass: Get the current loss function.
getLossFunction() - Method in class moa.classifiers.functions.SPegasos: Get the current loss function.
getLowerQuartile(int) - Method in class moa.evaluation.MeasureCollection
getMaxAttValsObserved() - Method in class moa.classifiers.core.attributeclassobservers.NominalAttributeClassObserver
getMaxInclusionProbability(Instance) - Method in class moa.cluster.Clustering
getMAXIndexes() - Method in class moa.classifiers.meta.DACC: Returns the classifiers that vote for the final prediction when the MAX combination function is selected
getMaxInstInLeaf() - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Get the maximum number of instances in a leaf.
getMaxRating() - Method in class moa.recommender.rc.data.impl.MemRecommenderData
getMaxRating() - Method in interface moa.recommender.rc.data.RecommenderData
getMaxRelativeNodeWidth(double[][], double[][]) - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Returns the maximum attribute width of instances/points in a KDTreeNode relative to the whole dataset.
getMaxValue(int) - Method in class moa.evaluation.MeasureCollection
getMaxValue() - Method in class moa.options.FloatOption
getMaxValue() - Method in class moa.options.IntOption
getMean() - Method in class moa.core.GaussianEstimator
getMean(int) - Method in class moa.evaluation.MeasureCollection
getMeanError() - Method in class moa.evaluation.BasicRegressionPerformanceEvaluator
getMeanError() - Method in class moa.evaluation.WindowRegressionPerformanceEvaluator
getMeanRunningTime() - Method in class moa.evaluation.MeasureCollection
getMeasure(String) - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Returns the value of the named measure.
getMeasureCollection() - Method in enum moa.gui.PreviewPanel.TypePanel
getMeasurement(int, int) - Method in class moa.evaluation.LearningCurve
getMeasurementName(int) - Method in class moa.evaluation.LearningCurve
getMeasurementNamed(String, Measurement[]) - Static method in class moa.core.Measurement
getMeasurements() - Method in class moa.evaluation.LearningEvaluation
getMeasurementsDescription(Measurement[], StringBuilder, int) - Static method in class moa.core.Measurement
getMeasurePerformance() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch: Gets whether performance statistics are being calculated or not.
getMeasures() - Method in class moa.gui.clustertab.ClusteringSetupTab
getMeasures() - Method in class moa.gui.outliertab.OutlierSetupTab
getMeasureSelected() - Method in class moa.gui.visualization.GraphCanvas
getMeasureValue(String) - Method in class moa.cluster.Cluster
getMeasureValue(String) - Method in class moa.gui.visualization.DataPoint
getMedian(int) - Method in class moa.evaluation.MeasureCollection
GetMemoryUsage() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
getMeritOfSplit(double[], double[][]) - Method in class moa.classifiers.core.splitcriteria.GiniSplitCriterion
getMeritOfSplit(double[], double[][]) - Method in class moa.classifiers.core.splitcriteria.InfoGainSplitCriterion
getMeritOfSplit(double[], double[][]) - Method in interface moa.classifiers.core.splitcriteria.SplitCriterion: Computes the merit of splitting for a given ditribution before the split and after it.
getMeritOfSplit(double[], double[][]) - Method in class moa.classifiers.core.splitcriteria.VarianceReductionSplitCriterion
getMeritOfSplit(double[], double[][]) - Method in class moa.classifiers.rules.core.splitcriteria.SDRSplitCriterionAMRules
getMessage() - Method in class moa.streams.clustering.ClusterEvent
getMicroClustering() - Method in class moa.streams.clustering.RandomRBFGeneratorEvents
getMicroClusteringResult() - Method in class moa.clusterers.AbstractClusterer
getMicroClusteringResult() - Method in interface moa.clusterers.Clusterer
getMicroClusteringResult() - Method in class moa.clusterers.ClusterGenerator
getMicroClusteringResult() - Method in class moa.clusterers.clustream.Clustream
getMicroClusteringResult() - Method in class moa.clusterers.clustream.WithKmeans
getMicroClusteringResult() - Method in class moa.clusterers.clustree.ClusTree
getMicroClusteringResult() - Method in class moa.clusterers.denstream.WithDBSCAN
getMicroClusteringResult() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
getMicroClusters() - Method in interface moa.clusterers.macro.IDenseMacroCluster
getMicroClusters() - Method in class moa.clusterers.macro.NonConvexCluster
getMiddle(double[]) - Method in class moa.classifiers.lazy.neighboursearch.EuclideanDistance: Returns value in the middle of the two parameter values.
getMinBoxRelWidth() - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Gets the minimum relative box width.
getMinimumValue() - Method in class moa.classifiers.rules.driftdetection.PageHinkleyTest
GetMinPrecNeigh(Long) - Method in class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
GetMinPrecNeigh(Long) - Method in class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBNode
getMinRating() - Method in class moa.recommender.rc.data.impl.MemRecommenderData
getMinRating() - Method in interface moa.recommender.rc.data.RecommenderData
getMinValue(int) - Method in class moa.evaluation.MeasureCollection
getMinValue() - Method in class moa.options.FloatOption
getMinValue() - Method in class moa.options.IntOption
getModelAttIndexToInstanceAttIndex(int, Instance) - Method in class moa.classifiers.rules.AbstractAMRules
getModelContext() - Method in class moa.classifiers.AbstractClassifier
getModelContext() - Method in interface moa.classifiers.Classifier: Gets the reference to the header of the data stream.
getModelContext() - Method in class moa.clusterers.AbstractClusterer
getModelContext() - Method in interface moa.clusterers.Clusterer
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.AbstractClassifier: Returns a string representation of the model.
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.active.ActiveClassifier
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.bayes.NaiveBayes
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.bayes.NaiveBayesMultinomial
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.drift.DriftDetectionMethodClassifier
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.functions.MajorityClass
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.functions.NoChange
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.functions.Perceptron
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.functions.SGD
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.functions.SGDMultiClass
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.functions.SPegasos
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.lazy.kNN
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.lazy.kNNwithPAW
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.lazy.kNNwithPAWandADWIN
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.AccuracyUpdatedEnsemble
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.AccuracyWeightedEnsemble
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.ADACC
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.DACC
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.LeveragingBag
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.LimAttClassifier
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.OCBoost
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.OnlineSmoothBoost
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.OzaBag
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.OzaBagAdwin
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.OzaBagASHT
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.OzaBoost
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.OzaBoostAdwin
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.RandomRules
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.TemporallyAugmentedClassifier
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.WeightedMajorityAlgorithm
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.WEKAClassifier
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.multilabel.MajorityLabelset
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.rules.AbstractAMRules: print GUI learn model
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.rules.AMRulesRegressor
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.rules.functions.Perceptron
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.rules.functions.TargetMean
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.rules.RuleClassifier
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.trees.DecisionStump
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.trees.FIMTDD.FIMTDDPerceptron
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.trees.FIMTDD
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.trees.HoeffdingOptionTree
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.trees.HoeffdingTree
getModelDescription(StringBuilder, int) - Method in class moa.classifiers.trees.ORTO
getModelDescription(StringBuilder, int) - Method in class moa.clusterers.AbstractClusterer
getModelDescription(StringBuilder, int) - Method in class moa.clusterers.ClusterGenerator
getModelDescription(StringBuilder, int) - Method in class moa.clusterers.clustream.Clustream
getModelDescription(StringBuilder, int) - Method in class moa.clusterers.clustream.WithKmeans
getModelDescription(StringBuilder, int) - Method in class moa.clusterers.clustree.ClusTree
getModelDescription(StringBuilder, int) - Method in class moa.clusterers.CobWeb
getModelDescription(StringBuilder, int) - Method in class moa.clusterers.denstream.WithDBSCAN
getModelDescription(StringBuilder, int) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
getModelDescription(StringBuilder, int) - Method in class moa.clusterers.streamkm.StreamKM
getModelDescription(StringBuilder, int) - Method in class moa.clusterers.WekaClusteringAlgorithm
getModelDescription(StringBuilder, int) - Method in class moa.learners.ChangeDetectorLearner
getModelDescriptionNoAnomalyDetection(StringBuilder, int) - Method in class moa.classifiers.rules.RuleClassifier
getModelMeasurements() - Method in class moa.classifiers.AbstractClassifier
getModelMeasurements() - Method in interface moa.classifiers.Classifier: Gets the current measurements of this classifier.
getModelMeasurements() - Method in class moa.clusterers.AbstractClusterer
getModelMeasurements() - Method in interface moa.clusterers.Clusterer
getModelMeasurementsImpl() - Method in class moa.classifiers.AbstractClassifier: Gets the current measurements of this classifier.

The reason for ...Impl methods: ease programmer burden by not requiring them to remember calls to super in overridden methods.
getModelMeasurementsImpl() - Method in class moa.classifiers.active.ActiveClassifier
getModelMeasurementsImpl() - Method in class moa.classifiers.bayes.NaiveBayes
getModelMeasurementsImpl() - Method in class moa.classifiers.bayes.NaiveBayesMultinomial
getModelMeasurementsImpl() - Method in class moa.classifiers.drift.DriftDetectionMethodClassifier
getModelMeasurementsImpl() - Method in class moa.classifiers.functions.MajorityClass
getModelMeasurementsImpl() - Method in class moa.classifiers.functions.NoChange
getModelMeasurementsImpl() - Method in class moa.classifiers.functions.Perceptron
getModelMeasurementsImpl() - Method in class moa.classifiers.functions.SGD
getModelMeasurementsImpl() - Method in class moa.classifiers.functions.SGDMultiClass
getModelMeasurementsImpl() - Method in class moa.classifiers.functions.SPegasos
getModelMeasurementsImpl() - Method in class moa.classifiers.lazy.kNN
getModelMeasurementsImpl() - Method in class moa.classifiers.meta.AccuracyUpdatedEnsemble: Adds ensemble weights to the measurements.
getModelMeasurementsImpl() - Method in class moa.classifiers.meta.AccuracyWeightedEnsemble: Adds ensemble weights to the measurements.
getModelMeasurementsImpl() - Method in class moa.classifiers.meta.ADACC
getModelMeasurementsImpl() - Method in class moa.classifiers.meta.DACC
getModelMeasurementsImpl() - Method in class moa.classifiers.meta.LeveragingBag
getModelMeasurementsImpl() - Method in class moa.classifiers.meta.LimAttClassifier
getModelMeasurementsImpl() - Method in class moa.classifiers.meta.OCBoost
getModelMeasurementsImpl() - Method in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble: Adds ensemble weights to the measurements.
getModelMeasurementsImpl() - Method in class moa.classifiers.meta.OnlineSmoothBoost
getModelMeasurementsImpl() - Method in class moa.classifiers.meta.OzaBag
getModelMeasurementsImpl() - Method in class moa.classifiers.meta.OzaBagAdwin
getModelMeasurementsImpl() - Method in class moa.classifiers.meta.OzaBoost
getModelMeasurementsImpl() - Method in class moa.classifiers.meta.OzaBoostAdwin
getModelMeasurementsImpl() - Method in class moa.classifiers.meta.RandomRules
getModelMeasurementsImpl() - Method in class moa.classifiers.meta.TemporallyAugmentedClassifier
getModelMeasurementsImpl() - Method in class moa.classifiers.meta.WeightedMajorityAlgorithm
getModelMeasurementsImpl() - Method in class moa.classifiers.meta.WEKAClassifier
getModelMeasurementsImpl() - Method in class moa.classifiers.multilabel.MajorityLabelset
getModelMeasurementsImpl() - Method in class moa.classifiers.rules.AbstractAMRules: print GUI evaluate model
getModelMeasurementsImpl() - Method in class moa.classifiers.rules.functions.Perceptron
getModelMeasurementsImpl() - Method in class moa.classifiers.rules.functions.TargetMean
getModelMeasurementsImpl() - Method in class moa.classifiers.rules.RuleClassifier
getModelMeasurementsImpl() - Method in class moa.classifiers.trees.DecisionStump
getModelMeasurementsImpl() - Method in class moa.classifiers.trees.FIMTDD
getModelMeasurementsImpl() - Method in class moa.classifiers.trees.HoeffdingOptionTree
getModelMeasurementsImpl() - Method in class moa.classifiers.trees.HoeffdingTree
getModelMeasurementsImpl() - Method in class moa.classifiers.trees.ORTO
getModelMeasurementsImpl() - Method in class moa.clusterers.AbstractClusterer
getModelMeasurementsImpl() - Method in class moa.clusterers.ClusterGenerator
getModelMeasurementsImpl() - Method in class moa.clusterers.clustream.Clustream
getModelMeasurementsImpl() - Method in class moa.clusterers.clustream.WithKmeans
getModelMeasurementsImpl() - Method in class moa.clusterers.clustree.ClusTree
getModelMeasurementsImpl() - Method in class moa.clusterers.CobWeb
getModelMeasurementsImpl() - Method in class moa.clusterers.denstream.WithDBSCAN
getModelMeasurementsImpl() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
getModelMeasurementsImpl() - Method in class moa.clusterers.streamkm.StreamKM
getModelMeasurementsImpl() - Method in class moa.clusterers.WekaClusteringAlgorithm
getModelMeasurementsImpl() - Method in class moa.learners.ChangeDetectorLearner
getModelQuality() - Method in class moa.evaluation.CMM_GTAnalysis: Calculates the relative number of errors being caused by the underlying cluster model
getN() - Method in class moa.cluster.CFCluster
getName() - Method in class moa.clusterers.clustream.Clustream
getName() - Method in class moa.clusterers.clustream.WithKmeans
getName(int) - Static method in class moa.clusterers.macro.ColorArray
getName() - Method in class moa.clusterers.macro.ColorObject
getName() - Method in class moa.core.Measurement
getName(int) - Method in class moa.evaluation.MeasureCollection
getName() - Method in class moa.options.AbstractOption
getName() - Method in interface moa.options.Option: Gets the name of this option
getNames() - Method in class moa.evaluation.Accuracy
getNames() - Method in class moa.evaluation.ChangeDetectionMeasures
getNames() - Method in class moa.evaluation.CMM
getNames() - Method in class moa.evaluation.EntropyCollection
getNames() - Method in class moa.evaluation.F1
getNames() - Method in class moa.evaluation.General
getNames() - Method in class moa.evaluation.MeasureCollection
getNames() - Method in class moa.evaluation.OutlierPerformance
getNames() - Method in class moa.evaluation.RegressionAccuracy
getNames() - Method in class moa.evaluation.SilhouetteCoefficient
getNames() - Method in class moa.evaluation.SSQ
getNames() - Method in class moa.evaluation.StatisticalCollection
getNanoCPUTimeOfCurrentThread() - Static method in class moa.core.TimingUtils
getNanoCPUTimeOfThread(long) - Static method in class moa.core.TimingUtils
getNbActiveClassifiers() - Method in class moa.classifiers.meta.ADACC
getNbActiveClassifiers() - Method in class moa.classifiers.meta.DACC: Returns the number of classifiers used for prediction which includes the adaptive learners and the snapshots in ADACC
getNbAdaptiveClassifiers() - Method in class moa.classifiers.meta.ADACC
getNbAdaptiveClassifiers() - Method in class moa.classifiers.meta.DACC: Returns the number of adaptive classifiers in the ensemble which excludes the static snapshots in ADACC
getNearest(DATA, double, int) - Method in class moa.clusterers.outliers.utils.mtree.MTree: Performs a nearest-neighbor query on the M-Tree, constrained by distance and/or the number of neighbors.
getNearest(DATA) - Method in class moa.clusterers.outliers.utils.mtree.MTree: Performs a nearest-neighbor query on the M-Tree, without constraints.
getNearestByLimit(DATA, int) - Method in class moa.clusterers.outliers.utils.mtree.MTree: Performs a nearest-neighbors query on the M-Tree, constrained by the number of neighbors.
getNearestByRange(DATA, double) - Method in class moa.clusterers.outliers.utils.mtree.MTree: Performs a nearest-neighbors query on the M-Tree, constrained by distance.
getNewMeasureCollection() - Method in class moa.gui.TaskTextViewerPanel
getNext() - Method in class moa.classifiers.meta.LimAttClassifier.CombinationGenerator
getNode() - Method in class moa.clusterers.clustree.Entry
getNodeList() - Method in class moa.classifiers.rules.core.Rule
GetNodesCount() - Method in class moa.clusterers.outliers.MCOD.MicroCluster
getNodeSplitter() - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Returns the splitting method currently in use to split the nodes of the KDTree.
getNodeStatistics() - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
getNoiseLabel() - Method in class moa.gui.visualization.DataPoint
getNoiseSeparability() - Method in class moa.evaluation.CMM_GTAnalysis: Calculates how well noise is separable from the given clusters Small values indicate bad separability, values close to 1 indicate good separability
getNominalValueString(int, int) - Method in class moa.classifiers.AbstractClassifier: Gets the name of a value of an attribute from the header.
getNominalValueString(int, int) - Method in class moa.clusterers.AbstractClusterer
getNominalValueString(InstancesHeader, int, int) - Static method in class moa.core.InstancesHeader
getNormalizedError(Instance) - Method in class moa.classifiers.trees.FIMTDD
getNormalizedPrediction(Instance) - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
getNormalizeNodeWidth() - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Gets the normalize flag.
getNrOfClasses() - Method in class moa.clusterers.outliers.AnyOut.util.DataSet: Counts the number of classes that are present in the data set.
getNrOfDimensions() - Method in class moa.clusterers.outliers.AnyOut.util.DataObject: Returns the number of features (label attribute excluded).
getNrOfDimensions() - Method in class moa.clusterers.outliers.AnyOut.util.DataSet: Return the dimension of the objects in the DataSet.
getNullString() - Method in class moa.options.AbstractClassOption: Gets the null string of this option.
getNumberAttributes() - Method in class moa.classifiers.functions.Perceptron
getNumberChanges() - Method in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
getNumberChangesOccurred() - Method in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
getNumberClasses() - Method in class moa.classifiers.functions.Perceptron
getNumberDetections() - Method in class moa.classifiers.core.driftdetection.ADWIN
getNumberDetections() - Method in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
getNumberOfGT0Classes() - Method in class moa.evaluation.CMM_GTAnalysis: Number of classes/clusters of the new clustering
getNumberOfValues(int) - Method in class moa.evaluation.MeasureCollection
getNumberVotes() - Method in class moa.classifiers.rules.core.voting.AbstractErrorWeightedVote
getNumberVotes() - Method in interface moa.classifiers.rules.core.voting.ErrorWeightedVote: The number of votes added so far.
getNumberWarnings() - Method in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
getNumBytesWritten() - Method in class moa.core.SerializeUtils.ByteCountingOutputStream
getNumClasses() - Method in class moa.evaluation.MembershipMatrix
getNumClassLabels() - Method in class moa.core.MultilabelInstancesHeader
getNumColors() - Static method in class moa.clusterers.macro.ColorArray
getNumericValueString(InstancesHeader, int, double) - Static method in class moa.core.InstancesHeader
getNumFeatures() - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
getNumItems() - Method in class moa.recommender.rc.data.impl.MemRecommenderData
getNumItems() - Method in interface moa.recommender.rc.data.RecommenderData
getNumLabels() - Method in class moa.core.MultilabelInstance
getNumLeft() - Method in class moa.classifiers.meta.LimAttClassifier.CombinationGenerator
getNumMeasures() - Method in class moa.evaluation.MeasureCollection
getNumRatings() - Method in class moa.recommender.rc.data.impl.MemRecommenderData
getNumRatings() - Method in interface moa.recommender.rc.data.RecommenderData
getNumRootSplits() - Method in class moa.clusterers.clustree.ClusTree: Return the number of time the tree has grown in size.
getNumSubtrees() - Method in class moa.classifiers.trees.ORTO.Node
getNumSubtrees() - Method in class moa.classifiers.trees.ORTO.OptionNode
getNumSubtrees() - Method in class moa.classifiers.trees.ORTO.SplitNode
getNumUsers() - Method in class moa.recommender.rc.data.impl.MemRecommenderData
getNumUsers() - Method in interface moa.recommender.rc.data.RecommenderData
getObject(int) - Method in class moa.clusterers.outliers.AnyOut.util.DataSet: Returns the DataObject at the given position.
getObject(String, String) - Static method in class moa.gui.GUIDefaults: Tries to instantiate the class stored for this property, optional options will be set as well.
getObject(String, String, Class) - Static method in class moa.gui.GUIDefaults: Tries to instantiate the class stored for this property, optional options will be set as well.
getObjectInfo(Object) - Method in class moa.clusterers.outliers.AbstractC.AbstractCBase
getObjectInfo(Object) - Method in class moa.clusterers.outliers.Angiulli.ApproxSTORM
getObjectInfo(Object) - Method in class moa.clusterers.outliers.Angiulli.ExactSTORM
getObjectInfo(Object) - Method in class moa.clusterers.outliers.AnyOut.AnyOut
getObjectInfo(Object) - Method in class moa.clusterers.outliers.MCOD.MCODBase
getObjectInfo(Object) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
getObjectInfo(Object) - Method in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
getObjectInfo() - Method in class moa.gui.visualization.PointPanel
getObjectNamed(String) - Method in interface moa.core.ObjectRepository
getObservedClassDistribution() - Method in class moa.classifiers.trees.HoeffdingOptionTree.Node
getObservedClassDistribution() - Method in class moa.classifiers.trees.HoeffdingTree.Node
getOption(String) - Method in class moa.options.Options
getOption(char) - Method in class moa.options.Options
getOptionArray() - Method in class moa.options.Options
getOptionLabels() - Method in class moa.options.MultiChoiceOption
getOptions() - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter: Gets the current settings of the object.
getOptions() - Method in class moa.clusterers.outliers.AnyOut.AnyOut
getOptions() - Method in class moa.options.AbstractOptionHandler
getOptions() - Method in interface moa.options.OptionHandler: Gets the options of this object
getOptions() - Method in class weka.classifiers.meta.MOA: Gets the current settings of the Classifier.
getOptions() - Method in class weka.datagenerators.classifiers.classification.MOA: Gets the current settings of the datagenerator.
getOrderingMeasurementName() - Method in class moa.evaluation.LearningCurve
getOutlierer0() - Method in class moa.gui.outliertab.OutlierSetupTab
getOutlierer1() - Method in class moa.gui.outliertab.OutlierSetupTab
getOutlierScore(int) - Method in class moa.clusterers.outliers.AnyOut.AnyOutCore
GetOutliersFound() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
getOutliersResult() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
getOutliersVisibility() - Method in class moa.gui.outliertab.OutlierVisualTab
getOutput() - Method in class moa.classifiers.core.driftdetection.AbstractChangeDetector: Gets the output state of the change detection.
getOutput() - Method in interface moa.classifiers.core.driftdetection.ChangeDetector: Gets the output state of the change detection.
getOwner() - Method in class moa.classifiers.rules.core.Rule.Builder
getParameterString() - Method in class moa.clusterers.denstream.WithDBSCAN
getParameterString() - Method in class moa.evaluation.CMM
getParameterString() - Method in class moa.evaluation.CMM_GTAnalysis: String with main CMM parameters
getParameterString() - Method in class moa.streams.clustering.RandomRBFGeneratorEvents
getParent() - Method in class moa.classifiers.trees.FIMTDD.Node: Return the parent node
getParent() - Method in class moa.classifiers.trees.ORTO.Node: Return the parent node
getParentEntry() - Method in class moa.clusterers.clustree.Entry
getPauseInterval() - Method in class moa.gui.clustertab.ClusteringVisualTab
getPauseInterval() - Method in class moa.gui.outliertab.OutlierVisualTab
getPerceptron() - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
getPerformanceMeasurements() - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator
getPerformanceMeasurements() - Method in class moa.evaluation.BasicClusteringPerformanceEvaluator
getPerformanceMeasurements() - Method in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
getPerformanceMeasurements() - Method in class moa.evaluation.BasicRegressionPerformanceEvaluator
getPerformanceMeasurements() - Method in interface moa.evaluation.ClassificationPerformanceEvaluator: Gets the current measurements monitored by this evaluator.
getPerformanceMeasurements() - Method in class moa.evaluation.EWMAClassificationPerformanceEvaluator
getPerformanceMeasurements() - Method in class moa.evaluation.FadingFactorClassificationPerformanceEvaluator
getPerformanceMeasurements() - Method in interface moa.evaluation.LearningPerformanceEvaluator
getPerformanceMeasurements() - Method in class moa.evaluation.MultilabelWindowClassificationPerformanceEvaluator
getPerformanceMeasurements() - Method in class moa.evaluation.WindowClassificationPerformanceEvaluator
getPerformanceMeasurements() - Method in class moa.evaluation.WindowRegressionPerformanceEvaluator
getPHError(Instance) - Method in class moa.classifiers.trees.ORTO.ActiveLearningNode
getPoint(int) - Method in class moa.evaluation.CMM_GTAnalysis: Get CMM internal point
getPointColorbyClass(DataPoint, float) - Static method in class moa.gui.visualization.PointPanel
getPointVisibility() - Method in class moa.gui.outliertab.OutlierVisualTab
getPrediction(Instance, int) - Method in class moa.classifiers.rules.core.Rule
getPrediction(Instance) - Method in class moa.classifiers.rules.core.Rule
getPrediction(Instance) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
getPrediction(Instance, int) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
getPrediction(Instance, int) - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
getPrediction(Instance, FIMTDD) - Method in class moa.classifiers.trees.FIMTDD.LeafNode
getPrediction(Instance, FIMTDD) - Method in class moa.classifiers.trees.FIMTDD.Node
getPrediction(Instance, FIMTDD) - Method in class moa.classifiers.trees.FIMTDD.SplitNode
getPrediction(Instance, ORTO) - Method in class moa.classifiers.trees.ORTO.ActiveLearningNode
getPrediction(Instance, ORTO) - Method in class moa.classifiers.trees.ORTO.Node
getPrediction(Instance, ORTO) - Method in class moa.classifiers.trees.ORTO.OptionNode
getPrediction(Instance, ORTO) - Method in class moa.classifiers.trees.ORTO.SplitNode
getPredictionError() - Method in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
getPredictionModel(Instance, FIMTDD) - Method in class moa.classifiers.trees.FIMTDD.LeafNode: Retrieve the class votes using the perceptron learner
getPredictionTargetMean(Instance, FIMTDD) - Method in class moa.classifiers.trees.FIMTDD.LeafNode
getPreferredSize() - Method in class moa.gui.visualization.GraphCurve
getPreMaterializedObject() - Method in class moa.options.AbstractClassOption: Returns the current object.
getPreparedClassOption(ClassOption) - Method in class moa.options.AbstractOptionHandler: Gets a prepared option of this class.
getPreparedClassOption(ClassOptionWithNames) - Method in class moa.options.AbstractOptionHandler: Gets a prepared option of this class.
getPreview(ResultPreviewListener) - Method in class moa.tasks.TaskThread
getProcessFrequency() - Method in class moa.gui.visualization.GraphCanvas
getProgressFraction() - Method in class moa.core.InputStreamProgressMonitor
getProperties() - Static method in class moa.gui.GUIDefaults: returns the associated properties file.
getPropotionBelow(double) - Method in class moa.core.GreenwaldKhannaQuantileSummary
getPurpose() - Method in class moa.options.AbstractOption
getPurpose() - Method in interface moa.options.Option: Gets the purpose of this option
getPurposeString() - Method in class moa.classifiers.AbstractClassifier
getPurposeString() - Method in class moa.classifiers.active.ActiveClassifier
getPurposeString() - Method in class moa.classifiers.bayes.NaiveBayes
getPurposeString() - Method in class moa.classifiers.bayes.NaiveBayesMultinomial
getPurposeString() - Method in class moa.classifiers.drift.DriftDetectionMethodClassifier
getPurposeString() - Method in class moa.classifiers.functions.MajorityClass
getPurposeString() - Method in class moa.classifiers.functions.NoChange
getPurposeString() - Method in class moa.classifiers.functions.Perceptron
getPurposeString() - Method in class moa.classifiers.functions.SGD
getPurposeString() - Method in class moa.classifiers.functions.SGDMultiClass
getPurposeString() - Method in class moa.classifiers.functions.SPegasos
getPurposeString() - Method in class moa.classifiers.lazy.kNN
getPurposeString() - Method in class moa.classifiers.lazy.kNNwithPAW
getPurposeString() - Method in class moa.classifiers.lazy.kNNwithPAWandADWIN
getPurposeString() - Method in class moa.classifiers.meta.AccuracyWeightedEnsemble
getPurposeString() - Method in class moa.classifiers.meta.ADACC
getPurposeString() - Method in class moa.classifiers.meta.DACC
getPurposeString() - Method in class moa.classifiers.meta.LeveragingBag
getPurposeString() - Method in class moa.classifiers.meta.LimAttClassifier
getPurposeString() - Method in class moa.classifiers.meta.OCBoost
getPurposeString() - Method in class moa.classifiers.meta.OnlineSmoothBoost
getPurposeString() - Method in class moa.classifiers.meta.OzaBag
getPurposeString() - Method in class moa.classifiers.meta.OzaBagAdwin
getPurposeString() - Method in class moa.classifiers.meta.OzaBagASHT
getPurposeString() - Method in class moa.classifiers.meta.OzaBoost
getPurposeString() - Method in class moa.classifiers.meta.OzaBoostAdwin
getPurposeString() - Method in class moa.classifiers.meta.RandomRules
getPurposeString() - Method in class moa.classifiers.meta.TemporallyAugmentedClassifier
getPurposeString() - Method in class moa.classifiers.meta.WeightedMajorityAlgorithm
getPurposeString() - Method in class moa.classifiers.meta.WEKAClassifier
getPurposeString() - Method in class moa.classifiers.rules.RuleClassifier
getPurposeString() - Method in class moa.classifiers.trees.AdaHoeffdingOptionTree
getPurposeString() - Method in class moa.classifiers.trees.ASHoeffdingTree
getPurposeString() - Method in class moa.classifiers.trees.DecisionStump
getPurposeString() - Method in class moa.classifiers.trees.FIMTDD.FIMTDDPerceptron
getPurposeString() - Method in class moa.classifiers.trees.FIMTDD
getPurposeString() - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree
getPurposeString() - Method in class moa.classifiers.trees.HoeffdingOptionTree
getPurposeString() - Method in class moa.classifiers.trees.HoeffdingTree
getPurposeString() - Method in class moa.classifiers.trees.LimAttHoeffdingTree
getPurposeString() - Method in class moa.classifiers.trees.ORTO
getPurposeString() - Method in class moa.classifiers.trees.RandomHoeffdingTree
getPurposeString() - Method in class moa.clusterers.AbstractClusterer
getPurposeString() - Method in class moa.clusterers.outliers.AnyOut.AnyOut
getPurposeString() - Method in class moa.clusterers.WekaClusteringAlgorithm
getPurposeString() - Method in class moa.options.AbstractOptionHandler
getPurposeString() - Method in interface moa.options.OptionHandler: Gets the purpose of this object
getPurposeString() - Method in class moa.recommender.dataset.impl.FlixsterDataset
getPurposeString() - Method in class moa.recommender.dataset.impl.JesterDataset
getPurposeString() - Method in class moa.recommender.dataset.impl.MovielensDataset
getPurposeString() - Method in class moa.streams.ArffFileStream
getPurposeString() - Method in class moa.streams.clustering.FileStream
getPurposeString() - Method in class moa.streams.clustering.RandomRBFGeneratorEvents
getPurposeString() - Method in class moa.streams.ConceptDriftRealStream
getPurposeString() - Method in class moa.streams.ConceptDriftStream
getPurposeString() - Method in class moa.streams.FilteredStream
getPurposeString() - Method in class moa.streams.filters.AddNoiseFilter
getPurposeString() - Method in class moa.streams.filters.CacheFilter
getPurposeString() - Method in class moa.streams.filters.ReplacingMissingValuesFilter
getPurposeString() - Method in class moa.streams.generators.AgrawalGenerator
getPurposeString() - Method in class moa.streams.generators.cd.AbstractConceptDriftGenerator
getPurposeString() - Method in class moa.streams.generators.HyperplaneGenerator
getPurposeString() - Method in class moa.streams.generators.LEDGenerator
getPurposeString() - Method in class moa.streams.generators.LEDGeneratorDrift
getPurposeString() - Method in class moa.streams.generators.multilabel.MetaMultilabelGenerator
getPurposeString() - Method in class moa.streams.generators.multilabel.MultilabelArffFileStream
getPurposeString() - Method in class moa.streams.generators.RandomRBFGenerator
getPurposeString() - Method in class moa.streams.generators.RandomRBFGeneratorDrift
getPurposeString() - Method in class moa.streams.generators.RandomTreeGenerator
getPurposeString() - Method in class moa.streams.generators.SEAGenerator
getPurposeString() - Method in class moa.streams.generators.STAGGERGenerator
getPurposeString() - Method in class moa.streams.generators.WaveformGenerator
getPurposeString() - Method in class moa.streams.generators.WaveformGeneratorDrift
getPurposeString() - Method in class moa.streams.MultiFilteredStream
getPurposeString() - Method in class moa.tasks.CacheShuffledStream
getPurposeString() - Method in class moa.tasks.EvaluateClustering
getPurposeString() - Method in class moa.tasks.EvaluateConceptDrift
getPurposeString() - Method in class moa.tasks.EvaluateInterleavedChunks
getPurposeString() - Method in class moa.tasks.EvaluateInterleavedTestThenTrain
getPurposeString() - Method in class moa.tasks.EvaluateModel
getPurposeString() - Method in class moa.tasks.EvaluateModelRegression
getPurposeString() - Method in class moa.tasks.EvaluateOnlineRecommender
getPurposeString() - Method in class moa.tasks.EvaluatePeriodicHeldOutTest
getPurposeString() - Method in class moa.tasks.EvaluatePrequential
getPurposeString() - Method in class moa.tasks.EvaluatePrequentialRegression
getPurposeString() - Method in class moa.tasks.LearnModel
getPurposeString() - Method in class moa.tasks.LearnModelRegression
getPurposeString() - Method in class moa.tasks.MeasureStreamSpeed
getPurposeString() - Method in class moa.tasks.Plot
getPurposeString() - Method in class moa.tasks.RunStreamTasks
getPurposeString() - Method in class moa.tasks.RunTasks
getPurposeString() - Method in class moa.tasks.WriteStreamToARFFFile
getQuantile(double) - Method in class moa.core.GreenwaldKhannaQuantileSummary
getRadius() - Method in class moa.cluster.CFCluster: See interface Cluster
getRadius() - Method in class moa.cluster.SphereCluster
getRadius() - Method in class moa.clusterers.clustream.ClustreamKernel
getRadius() - Method in class moa.clusterers.clustree.ClusKernel: See interface Cluster
getRadius() - Method in class moa.clusterers.denstream.MicroCluster
getRadius(long) - Method in class moa.clusterers.denstream.MicroCluster
getRadius() - Method in class moa.clusterers.macro.NonConvexCluster
getRangeOfMerit(double[]) - Method in class moa.classifiers.core.splitcriteria.GiniSplitCriterion
getRangeOfMerit(double[]) - Method in class moa.classifiers.core.splitcriteria.InfoGainSplitCriterion
getRangeOfMerit(double[]) - Method in interface moa.classifiers.core.splitcriteria.SplitCriterion: Computes the range of splitting merit
getRangeOfMerit(double[]) - Method in class moa.classifiers.core.splitcriteria.VarianceReductionSplitCriterion
getRangeOfMerit(double[]) - Method in class moa.classifiers.rules.core.splitcriteria.SDRSplitCriterionAMRules
getRanges() - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Method to get the ranges.
getRating(int, int) - Method in class moa.recommender.rc.data.impl.MemRecommenderData
getRating(int, int) - Method in interface moa.recommender.rc.data.RecommenderData
getRatingsItem(int) - Method in class moa.recommender.rc.data.impl.MemRecommenderData
getRatingsItem(int) - Method in interface moa.recommender.rc.data.RecommenderData
getRatingsUser(int) - Method in class moa.recommender.rc.data.impl.MemRecommenderData
getRatingsUser(int) - Method in interface moa.recommender.rc.data.RecommenderData
getRawLevel() - Method in class moa.clusterers.clustree.Node: Return the level number in the node.
getRelevanceStamp() - Method in class moa.clusterers.clustream.ClustreamKernel
getRelevantLabels(Instance) - Method in class moa.core.utils.Converter
getRequiredType() - Method in class moa.options.AbstractClassOption: Gets the class type of this option.
getRevision() - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNode: Returns the revision string.
getRevision() - Method in class weka.classifiers.meta.MOA: Returns the revision string.
getRevision() - Method in class weka.datagenerators.classifiers.classification.MOA: Returns the revision string.
getRightStreamPanel() - Method in class moa.gui.clustertab.ClusteringVisualTab
getRightStreamPanel() - Method in class moa.gui.outliertab.OutlierVisualTab
getRowCount() - Method in class moa.gui.conceptdrift.CDTaskManagerPanel.TaskTableModel
getRowCount() - Method in class moa.gui.LineGraphViewPanel.PlotTableModel
getRowCount() - Method in class moa.gui.RegressionTaskManagerPanel.TaskTableModel
getRowCount() - Method in class moa.gui.TaskManagerPanel.TaskTableModel
getRuleMajorityClassIndex(RuleClassification) - Method in class moa.classifiers.rules.RuleClassifier
getRuleNumberID() - Method in class moa.classifiers.rules.core.Rule
getSaveInstanceData() - Method in class moa.clusterers.CobWeb: Get the value of saveInstances.
getSecond() - Method in class moa.recommender.rc.utils.Pair
getSelectedCurrenTask() - Method in class moa.gui.conceptdrift.CDTaskManagerPanel
getSelectedMeasures() - Method in class moa.gui.clustertab.ClusteringEvalPanel
getSelectedMeasures() - Method in class moa.gui.outliertab.OutlierEvalPanel
getSelectedTasks() - Method in class moa.gui.conceptdrift.CDTaskManagerPanel
getSelectedTasks() - Method in class moa.gui.RegressionTaskManagerPanel
getSelectedTasks() - Method in class moa.gui.TaskManagerPanel
getShapeToPlot() - Method in class moa.gui.LineGraphViewPanel.PlotLine
getSimplePrediction() - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
getSimplePrediction() - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
getSingleLineDescription(StringBuilder) - Method in class moa.core.DoubleVector
getSingleLineDescription(StringBuilder, int) - Method in class moa.core.DoubleVector
getSingleModeFlag() - Method in class weka.datagenerators.classifiers.classification.MOA: Return if single mode is set for the given data generator mode depends on option setting and or generator type.
getSkipIdentical() - Method in class moa.classifiers.lazy.neighboursearch.LinearNNSearch: Gets whether if identical instances are skipped from the neighbourhood.
GetSpeed() - Method in class moa.gui.outliertab.OutlierVisualTab
getSplitDim() - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNode: Gets the splitting dimension.
getSplitIndex() - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
getSplitPointSuggestions() - Method in class moa.classifiers.core.attributeclassobservers.GaussianNumericAttributeClassObserver
getSplitTest() - Method in class moa.classifiers.rules.nodes.RuleSplitNode
getSplitValue() - Method in class moa.classifiers.core.conditionaltests.NumericAttributeBinaryTest
getSplitValue() - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNode: Gets the splitting value.
getSplitValue() - Method in class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
getSquaredError() - Method in class moa.classifiers.trees.ORTO.ActiveLearningNode: Returns the squared error, for use in determining if an alternate tree is performing better than an original tree, or if the alternate tree should be deleted
getSquareError() - Method in class moa.evaluation.BasicRegressionPerformanceEvaluator
getSquareError() - Method in class moa.evaluation.WindowRegressionPerformanceEvaluator
getStackTraceString(Exception) - Static method in class moa.core.MiscUtils
getStateString() - Method in class moa.options.AbstractOption
getStateString() - Method in class moa.options.FlagOption
getStateString() - Method in interface moa.options.Option: Gets the state of this option in human readable form
getStatistics() - Method in class moa.clusterers.outliers.AbstractC.AbstractCBase
getStatistics() - Method in class moa.clusterers.outliers.Angiulli.STORMBase
getStatistics() - Method in class moa.clusterers.outliers.AnyOut.AnyOut
getStatistics() - Method in class moa.clusterers.outliers.MCOD.MCODBase
getStatistics() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
getStatistics() - Method in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
getStatisticsBranchSplit() - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
getStatisticsNewRuleActiveLearningNode() - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
getStatisticsOtherBranchSplit() - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
getStdDev() - Method in class moa.core.GaussianEstimator
getStream() - Method in class moa.gui.clustertab.ClusteringAlgoPanel
getStream() - Method in class moa.gui.outliertab.OutlierAlgoPanel
getStream0() - Method in class moa.gui.clustertab.ClusteringSetupTab
getStream0() - Method in class moa.gui.outliertab.OutlierSetupTab
getStreamValueAsCLIString() - Method in class moa.gui.clustertab.ClusteringAlgoPanel
getStreamValueAsCLIString() - Method in class moa.gui.outliertab.OutlierAlgoPanel
getStringValues() - Static method in enum moa.tasks.Plot.LegendLocation: Get string values for the enum values.
getStringValues() - Static method in enum moa.tasks.Plot.LegendType: Get string values for the enum values.
getStringValues() - Static method in enum moa.tasks.Plot.PlotStyle: Get string values for the enum values.
getStringValues() - Static method in enum moa.tasks.Plot.Terminal: Get string values for the enum values.
getSubClassifiers() - Method in class moa.classifiers.AbstractClassifier
getSubClassifiers() - Method in interface moa.classifiers.Classifier: Gets the classifiers of this ensemble.
getSubClassifiers() - Method in class moa.classifiers.meta.AccuracyUpdatedEnsemble
getSubClassifiers() - Method in class moa.classifiers.meta.AccuracyWeightedEnsemble
getSubClassifiers() - Method in class moa.classifiers.meta.DACC
getSubClassifiers() - Method in class moa.classifiers.meta.LeveragingBag
getSubClassifiers() - Method in class moa.classifiers.meta.LimAttClassifier
getSubClassifiers() - Method in class moa.classifiers.meta.OCBoost
getSubClassifiers() - Method in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble
getSubClassifiers() - Method in class moa.classifiers.meta.OnlineSmoothBoost
getSubClassifiers() - Method in class moa.classifiers.meta.OzaBag
getSubClassifiers() - Method in class moa.classifiers.meta.OzaBagAdwin
getSubClassifiers() - Method in class moa.classifiers.meta.OzaBoost
getSubClassifiers() - Method in class moa.classifiers.meta.OzaBoostAdwin
getSubClassifiers() - Method in class moa.classifiers.meta.RandomRules
getSubClassifiers() - Method in class moa.classifiers.meta.WeightedMajorityAlgorithm
getSubClusterers() - Method in class moa.clusterers.AbstractClusterer
getSubClusterers() - Method in interface moa.clusterers.Clusterer
getSuggestedCutpoints() - Method in class moa.core.GreenwaldKhannaQuantileSummary
getSVGString(int) - Method in class moa.gui.visualization.ClusterPanel
getSVGString(int) - Method in class moa.gui.visualization.OutlierPanel
getSVGString(int) - Method in class moa.gui.visualization.PointPanel
getSymbol() - Method in class moa.classifiers.rules.Predicates
getTableCellRendererComponent(JTable, Object, boolean, boolean, int, int) - Method in class moa.gui.conceptdrift.CDTaskManagerPanel.ProgressCellRenderer
getTableCellRendererComponent(JTable, Object, boolean, boolean, int, int) - Method in class moa.gui.RegressionTaskManagerPanel.ProgressCellRenderer
getTableCellRendererComponent(JTable, Object, boolean, boolean, int, int) - Method in class moa.gui.TaskManagerPanel.ProgressCellRenderer
getTabs() - Static method in class moa.gui.GUIDefaults: returns an array with the classnames of all the additional panels to display as tabs in the GUI.
getTabTitle() - Method in class moa.gui.AbstractTabPanel: Returns the string to display as title of the tab.
getTabTitle() - Method in class moa.gui.ClassificationTabPanel
getTabTitle() - Method in class moa.gui.clustertab.ClusteringTabPanel
getTabTitle() - Method in class moa.gui.ConceptDriftTabPanel
getTabTitle() - Method in class moa.gui.outliertab.OutlierTabPanel
getTabTitle() - Method in class moa.gui.RegressionTabPanel
getTargetMean() - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
getTargetMeanError() - Method in class moa.evaluation.BasicRegressionPerformanceEvaluator
getTargetSquareError() - Method in class moa.evaluation.BasicRegressionPerformanceEvaluator
getTask() - Method in class moa.tasks.TaskThread
getTaskName() - Method in class moa.tasks.AbstractTask: Gets the name of this task.
getTaskResultType() - Method in class moa.tasks.CacheShuffledStream
getTaskResultType() - Method in class moa.tasks.EvaluateClustering
getTaskResultType() - Method in class moa.tasks.EvaluateConceptDrift
getTaskResultType() - Method in class moa.tasks.EvaluateInterleavedChunks: Defines the task's result type.
getTaskResultType() - Method in class moa.tasks.EvaluateInterleavedTestThenTrain
getTaskResultType() - Method in class moa.tasks.EvaluateModel
getTaskResultType() - Method in class moa.tasks.EvaluateModelRegression
getTaskResultType() - Method in class moa.tasks.EvaluateOnlineRecommender
getTaskResultType() - Method in class moa.tasks.EvaluatePeriodicHeldOutTest
getTaskResultType() - Method in class moa.tasks.EvaluatePrequential
getTaskResultType() - Method in class moa.tasks.EvaluatePrequentialRegression
getTaskResultType() - Method in class moa.tasks.LearnModel
getTaskResultType() - Method in class moa.tasks.LearnModelRegression
getTaskResultType() - Method in class moa.tasks.MeasureStreamSpeed
getTaskResultType() - Method in class moa.tasks.Plot: Defines the task's result type.
getTaskResultType() - Method in class moa.tasks.RunStreamTasks
getTaskResultType() - Method in class moa.tasks.RunTasks
getTaskResultType() - Method in interface moa.tasks.Task: Gets the result type of this task.
getTaskResultType() - Method in class moa.tasks.WriteStreamToARFFFile
getTimePerObj() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
getTimestamp() - Method in class moa.clusterers.clustree.Entry: Return the current timestamp.
getTimestamp() - Method in class moa.clusterers.denstream.Timestamp
getTimestamp() - Method in class moa.gui.visualization.DataPoint
getTimestamp() - Method in class moa.streams.clustering.ClusterEvent
getToolTipText() - Method in class moa.gui.visualization.PointPanel
getTotal() - Method in class moa.classifiers.core.driftdetection.ADWIN
getTotal() - Method in class moa.classifiers.meta.LimAttClassifier.CombinationGenerator
getTotalCount() - Method in class moa.core.GreenwaldKhannaQuantileSummary
getTotalDelay() - Method in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
getTotalEntries() - Method in class moa.evaluation.MembershipMatrix
getTotalWeightObserved() - Method in class moa.core.GaussianEstimator
getTotalWeightObserved() - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator
getTotalWeightObserved() - Method in class moa.evaluation.BasicClusteringPerformanceEvaluator
getTotalWeightObserved() - Method in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
getTotalWeightObserved() - Method in class moa.evaluation.BasicRegressionPerformanceEvaluator
getTotalWeightObserved() - Method in class moa.evaluation.EWMAClassificationPerformanceEvaluator
getTotalWeightObserved() - Method in class moa.evaluation.FadingFactorClassificationPerformanceEvaluator
getTotalWeightObserved() - Method in class moa.evaluation.WindowClassificationPerformanceEvaluator
getTotalWeightObserved() - Method in class moa.evaluation.WindowRegressionPerformanceEvaluator
getType() - Method in class moa.streams.clustering.ClusterEvent
getUpperQuartile(int) - Method in class moa.evaluation.MeasureCollection
getUserFeatures(int) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
getUsers() - Method in class moa.recommender.rc.data.impl.MemRecommenderData
getUsers() - Method in interface moa.recommender.rc.data.RecommenderData
getValue() - Method in class moa.classifiers.meta.DACC.Pair
getValue() - Method in class moa.classifiers.rules.Predicates
getValue(int) - Method in class moa.core.DoubleVector
getValue() - Method in class moa.core.Measurement
getValue(int, int) - Method in class moa.evaluation.MeasureCollection
getValue() - Method in class moa.options.FloatOption
getValue() - Method in class moa.options.IntOption
getValue() - Method in class moa.options.StringOption
getValueAsCLIString() - Method in class moa.options.AbstractClassOption
getValueAsCLIString() - Method in class moa.options.ClassOption
getValueAsCLIString() - Method in class moa.options.ClassOptionWithNames
getValueAsCLIString() - Method in class moa.options.FlagOption
getValueAsCLIString() - Method in class moa.options.FloatOption
getValueAsCLIString() - Method in class moa.options.IntOption
getValueAsCLIString() - Method in class moa.options.ListOption
getValueAsCLIString() - Method in class moa.options.MultiChoiceOption
getValueAsCLIString() - Method in interface moa.options.Option: Gets the value of a Command Line Interface text as a string
getValueAsCLIString() - Method in class moa.options.StringOption
getValueAsCLIString() - Method in class moa.options.WEKAClassOption
getValueAt(int, int) - Method in class moa.gui.conceptdrift.CDTaskManagerPanel.TaskTableModel
getValueAt(int, int) - Method in class moa.gui.LineGraphViewPanel.PlotTableModel
getValueAt(int, int) - Method in class moa.gui.RegressionTaskManagerPanel.TaskTableModel
getValueAt(int, int) - Method in class moa.gui.TaskManagerPanel.TaskTableModel
getVariance() - Method in class moa.classifiers.core.driftdetection.ADWIN
getVariance() - Method in class moa.core.GaussianEstimator
getVariances() - Method in class moa.clusterers.outliers.AnyOut.util.DataSet: Calculates the variance of this data set for each dimension
getVarianceVector() - Method in class moa.clusterers.clustree.ClusKernel
getVotesForInstance(Instance) - Method in class moa.classifiers.active.ActiveClassifier
getVotesForInstance(Instance) - Method in class moa.classifiers.bayes.NaiveBayes
getVotesForInstance(Instance) - Method in class moa.classifiers.bayes.NaiveBayesMultinomial: Calculates the class membership probabilities for the given test instance.
getVotesForInstance(Instance) - Method in interface moa.classifiers.Classifier: Predicts the class memberships for a given instance.
getVotesForInstance(Instance) - Method in class moa.classifiers.drift.DriftDetectionMethodClassifier
getVotesForInstance(Instance) - Method in class moa.classifiers.functions.MajorityClass
getVotesForInstance(Instance) - Method in class moa.classifiers.functions.NoChange
getVotesForInstance(Instance) - Method in class moa.classifiers.functions.Perceptron
getVotesForInstance(Instance) - Method in class moa.classifiers.functions.SGD: Calculates the class membership probabilities for the given test instance.
getVotesForInstance(Instance) - Method in class moa.classifiers.functions.SGDMultiClass: Calculates the class membership probabilities for the given test instance.
getVotesForInstance(Instance) - Method in class moa.classifiers.functions.SPegasos: Calculates the class membership probabilities for the given test instance.
getVotesForInstance(Instance) - Method in class moa.classifiers.lazy.kNN
getVotesForInstance(Instance) - Method in class moa.classifiers.meta.AccuracyUpdatedEnsemble: Predicts a class for an example.
getVotesForInstance(Instance) - Method in class moa.classifiers.meta.AccuracyWeightedEnsemble: Predicts a class for an example.
getVotesForInstance(Instance) - Method in class moa.classifiers.meta.DACC
getVotesForInstance(Instance) - Method in class moa.classifiers.meta.LeveragingBag
getVotesForInstance(Instance) - Method in class moa.classifiers.meta.LimAttClassifier
getVotesForInstance(Instance) - Method in class moa.classifiers.meta.OCBoost
getVotesForInstance(Instance) - Method in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble: Predicts a class for an example.
getVotesForInstance(Instance) - Method in class moa.classifiers.meta.OnlineSmoothBoost
getVotesForInstance(Instance) - Method in class moa.classifiers.meta.OzaBag
getVotesForInstance(Instance) - Method in class moa.classifiers.meta.OzaBagAdwin
getVotesForInstance(Instance) - Method in class moa.classifiers.meta.OzaBagASHT
getVotesForInstance(Instance) - Method in class moa.classifiers.meta.OzaBoost
getVotesForInstance(Instance) - Method in class moa.classifiers.meta.OzaBoostAdwin
getVotesForInstance(Instance) - Method in class moa.classifiers.meta.RandomRules
getVotesForInstance(Instance) - Method in class moa.classifiers.meta.TemporallyAugmentedClassifier
getVotesForInstance(Instance) - Method in class moa.classifiers.meta.WeightedMajorityAlgorithm
getVotesForInstance(Instance) - Method in class moa.classifiers.meta.WEKAClassifier
getVotesForInstance(Instance) - Method in class moa.classifiers.multilabel.MajorityLabelset
getVotesForInstance(Instance) - Method in class moa.classifiers.multilabel.meta.MLOzaBag
getVotesForInstance(Instance) - Method in class moa.classifiers.multilabel.meta.MLOzaBagAdwin
getVotesForInstance(Instance) - Method in class moa.classifiers.multilabel.MultilabelHoeffdingTree
getVotesForInstance(Instance) - Method in class moa.classifiers.rules.AbstractAMRules: getVotesForInstance extension of the instance method getVotesForInstance in moa.classifier.java returns the prediction of the instance.
getVotesForInstance(Instance) - Method in class moa.classifiers.rules.functions.FadingTargetMean
getVotesForInstance(Instance) - Method in class moa.classifiers.rules.functions.Perceptron
getVotesForInstance(Instance) - Method in class moa.classifiers.rules.functions.TargetMean
getVotesForInstance(Instance) - Method in class moa.classifiers.rules.RuleClassifier
getVotesForInstance(Instance) - Method in class moa.classifiers.rules.RuleClassifierNBayes
getVotesForInstance(Instance) - Method in class moa.classifiers.trees.DecisionStump
getVotesForInstance(Instance) - Method in class moa.classifiers.trees.FIMTDD
getVotesForInstance(Instance) - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree
getVotesForInstance(Instance) - Method in class moa.classifiers.trees.HoeffdingOptionTree
getVotesForInstance(Instance) - Method in class moa.classifiers.trees.HoeffdingTree
getVotesForInstance(Instance) - Method in class moa.classifiers.trees.ORTO
getVotesForInstance(Instance) - Method in interface moa.clusterers.Clusterer
getVotesForInstance(Instance) - Method in class moa.clusterers.ClusterGenerator
getVotesForInstance(Instance) - Method in class moa.clusterers.clustream.Clustream
getVotesForInstance(Instance) - Method in class moa.clusterers.clustream.WithKmeans
getVotesForInstance(Instance) - Method in class moa.clusterers.clustree.ClusTree
getVotesForInstance(Instance) - Method in class moa.clusterers.CobWeb: Classifies a given instance.
getVotesForInstance(Instance) - Method in class moa.clusterers.denstream.WithDBSCAN
getVotesForInstance(Instance) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
getVotesForInstance(Instance) - Method in class moa.clusterers.streamkm.StreamKM
getVotesForInstance(Instance) - Method in class moa.clusterers.WekaClusteringAlgorithm
getVotesForInstance(Instance) - Method in class moa.learners.ChangeDetectorLearner
getVotesForInstanceBinary(Instance) - Method in class moa.classifiers.meta.LeveragingBag
getVotesForInstanceBinary(Instance) - Method in class moa.classifiers.meta.OzaBoostAdwin
getVotesForInstancePerceptron(double[][], int[], int) - Method in class moa.classifiers.meta.LimAttClassifier
getWaitWinFull() - Method in class moa.gui.outliertab.OutlierVisualTab
getWarning() - Method in class moa.classifiers.core.driftdetection.ADWIN
getWarningZone() - Method in class moa.classifiers.core.driftdetection.AbstractChangeDetector: Gets whether the change detector is in the warning zone, after a warning alert and before a change alert.
getWarningZone() - Method in interface moa.classifiers.core.driftdetection.ChangeDetector: Gets whether the change detector is in the warning zone, after a warning alert and before a change alert.
getWeight() - Method in class moa.cluster.CFCluster: See interface Cluster
getWeight() - Method in class moa.cluster.Cluster: Returns the weight of this cluster, not neccessarily normalized.
getWeight() - Method in class moa.cluster.SphereCluster
getWeight() - Method in class moa.clusterers.clustree.ClusKernel
getWeight() - Method in class moa.clusterers.denstream.MicroCluster
getWeightedError() - Method in class moa.classifiers.rules.core.voting.AbstractErrorWeightedVote
getWeightedError() - Method in interface moa.classifiers.rules.core.voting.ErrorWeightedVote: Returns the weighted error.
getWeights() - Method in class moa.classifiers.functions.Perceptron
getWeights() - Method in class moa.classifiers.rules.core.voting.AbstractErrorWeightedVote
getWeights() - Method in interface moa.classifiers.rules.core.voting.ErrorWeightedVote: Return the weights error.
getWeights() - Method in class moa.classifiers.rules.functions.Perceptron
getWeights() - Method in class moa.classifiers.trees.FIMTDD.FIMTDDPerceptron
getWeights() - Method in class moa.classifiers.trees.ORTO.ORTOPerceptron
getWeightSeen() - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
getWeightSeen() - Method in class moa.classifiers.rules.RuleClassifier
getWeightSeen() - Method in class moa.classifiers.trees.HoeffdingOptionTree.ActiveLearningNode
getWeightSeen() - Method in class moa.classifiers.trees.HoeffdingTree.ActiveLearningNode
getWeightSeenAtLastSplitEvaluation() - Method in class moa.classifiers.trees.HoeffdingOptionTree.ActiveLearningNode
getWeightSeenAtLastSplitEvaluation() - Method in class moa.classifiers.trees.HoeffdingTree.ActiveLearningNode
getWidth() - Method in class moa.classifiers.core.driftdetection.ADWIN
getWidthT() - Method in class moa.classifiers.core.driftdetection.ADWIN
getWorkbenchInfoString() - Static method in class moa.core.Globals
getWorstError() - Method in class moa.core.GreenwaldKhannaQuantileSummary
getWVDIndexes() - Method in class moa.classifiers.meta.DACC: Returns the classifiers that vote for the final prediction when the WVD combination function is selected
GiniSplitCriterion - Class in moa.classifiers.core.splitcriteria: Class for computing splitting criteria using Gini with respect to distributions of class values.
GiniSplitCriterion() - Constructor for class moa.classifiers.core.splitcriteria.GiniSplitCriterion
globalInfo() - Method in class moa.classifiers.lazy.neighboursearch.EuclideanDistance: Returns a string describing this object.
globalInfo() - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Returns a string describing this nearest neighbour search algorithm.
globalInfo() - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KMeansInpiredMethod: Returns a string describing this nearest neighbour search algorithm.
globalInfo() - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.MedianOfWidestDimension: Returns a string describing this nearest neighbour search algorithm.
globalInfo() - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.MidPointOfWidestDimension: Returns a string describing this nearest neighbour search algorithm.
globalInfo() - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.SlidingMidPointOfWidestSide: Returns a string describing this nearest neighbour search algorithm.
globalInfo() - Method in class moa.classifiers.lazy.neighboursearch.LinearNNSearch: Returns a string describing this nearest neighbour search algorithm.
globalInfo() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch: Returns a string describing this nearest neighbour search algorithm.
globalInfo() - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Returns a string describing this object.
globalInfo() - Method in class weka.classifiers.meta.MOA: Returns a string describing the classifier.
globalInfo() - Method in class weka.datagenerators.classifiers.classification.MOA: Returns a string describing this data generator.
Globals - Class in moa.core: Class for storing global information about current version of MOA.
Globals() - Constructor for class moa.core.Globals
gnuplotPathOption - Variable in class moa.tasks.Plot: Path to gunplot's binary directory, for example C:\Tools\Gnuplot\binary.
gracePeriodOption - Variable in class moa.classifiers.rules.AbstractAMRules
gracePeriodOption - Variable in class moa.classifiers.rules.RuleClassifier
gracePeriodOption - Variable in class moa.classifiers.trees.DecisionStump
gracePeriodOption - Variable in class moa.classifiers.trees.FIMTDD
gracePeriodOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree
gracePeriodOption - Variable in class moa.classifiers.trees.HoeffdingTree
gracePeriodOption - Variable in class moa.classifiers.trees.ORTO
GradualChangeGenerator - Class in moa.streams.generators.cd
GradualChangeGenerator() - Constructor for class moa.streams.generators.cd.GradualChangeGenerator
graph() - Method in class moa.clusterers.CobWeb: Generates the graph string of the Cobweb tree
GraphAxes - Class in moa.gui.visualization
GraphAxes() - Constructor for class moa.gui.visualization.GraphAxes: Creates new form GraphAxes
GraphCanvas - Class in moa.gui.visualization
GraphCanvas() - Constructor for class moa.gui.visualization.GraphCanvas: Creates new form GraphCanvas
GraphCurve - Class in moa.gui.visualization
GraphCurve() - Constructor for class moa.gui.visualization.GraphCurve: Creates new form GraphCurve
greaterThan - Variable in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserverRegression.Node
GreenwaldKhannaNumericAttributeClassObserver - Class in moa.classifiers.core.attributeclassobservers: Class for observing the class data distribution for a numeric attribute using Greenwald and Khanna methodology.
GreenwaldKhannaNumericAttributeClassObserver() - Constructor for class moa.classifiers.core.attributeclassobservers.GreenwaldKhannaNumericAttributeClassObserver
GreenwaldKhannaQuantileSummary - Class in moa.core: Class for representing summaries of Greenwald and Khanna quantiles.
GreenwaldKhannaQuantileSummary(int) - Constructor for class moa.core.GreenwaldKhannaQuantileSummary
GreenwaldKhannaQuantileSummary.Tuple - Class in moa.core
GreenwaldKhannaQuantileSummary.Tuple(double, long, long) - Constructor for class moa.core.GreenwaldKhannaQuantileSummary.Tuple
GreenwaldKhannaQuantileSummary.Tuple(double) - Constructor for class moa.core.GreenwaldKhannaQuantileSummary.Tuple
gridBagConstraints - Variable in class moa.gui.TaskTextViewerPanel
growthAllowed - Variable in class moa.classifiers.trees.HoeffdingTree
GUI - Class in moa.gui: The main class for the MOA gui.
GUI() - Constructor for class moa.gui.GUI
GUIDefaults - Class in moa.gui: This class offers get methods for the default GUI settings in the props file moa/gui/GUI.props.
GUIDefaults() - Constructor for class moa.gui.GUIDefaults
GUIUtils - Class in moa.gui: This class offers util methods for displaying dialogs showing errors or exceptions.
GUIUtils() - Constructor for class moa.gui.GUIUtils

H

hasEmptyConstructor(Class<?>) - Static method in class moa.core.AutoClassDiscovery
Hash - Class in moa.recommender.rc.utils
Hash() - Constructor for class moa.recommender.rc.utils.Hash
hashCode() - Method in class moa.clusterers.outliers.AbstractC.StreamObj
hashCode() - Method in class moa.clusterers.outliers.Angiulli.StreamObj
hashCode() - Method in class moa.clusterers.outliers.MCOD.StreamObj
hashCode() - Method in class moa.clusterers.outliers.SimpleCOD.StreamObj
hashCode(int) - Static method in class moa.recommender.rc.utils.Hash
hasMore() - Method in class moa.classifiers.meta.LimAttClassifier.CombinationGenerator
hasMoreInstances() - Method in class moa.streams.ArffFileStream
hasMoreInstances() - Method in class moa.streams.CachedInstancesStream
hasMoreInstances() - Method in class moa.streams.clustering.FileStream
hasMoreInstances() - Method in class moa.streams.clustering.RandomRBFGeneratorEvents
hasMoreInstances() - Method in class moa.streams.ConceptDriftRealStream
hasMoreInstances() - Method in class moa.streams.ConceptDriftStream
hasMoreInstances() - Method in class moa.streams.FilteredStream
hasMoreInstances() - Method in class moa.streams.filters.AbstractStreamFilter
hasMoreInstances() - Method in class moa.streams.filters.CacheFilter
hasMoreInstances() - Method in class moa.streams.generators.AgrawalGenerator
hasMoreInstances() - Method in class moa.streams.generators.cd.AbstractConceptDriftGenerator
hasMoreInstances() - Method in class moa.streams.generators.HyperplaneGenerator
hasMoreInstances() - Method in class moa.streams.generators.LEDGenerator
hasMoreInstances() - Method in class moa.streams.generators.multilabel.MetaMultilabelGenerator
hasMoreInstances() - Method in class moa.streams.generators.RandomRBFGenerator
hasMoreInstances() - Method in class moa.streams.generators.RandomTreeGenerator
hasMoreInstances() - Method in class moa.streams.generators.SEAGenerator
hasMoreInstances() - Method in class moa.streams.generators.STAGGERGenerator
hasMoreInstances() - Method in class moa.streams.generators.WaveformGenerator
hasMoreInstances() - Method in interface moa.streams.InstanceStream: Gets whether this stream has more instances to output.
hasMoreInstances() - Method in class moa.streams.MultiFilteredStream
hasMoreTime() - Method in interface moa.clusterers.clustree.util.Budget: A function for the tree to ask if there is budget(time) left.
hasMoreTime() - Method in class moa.clusterers.clustree.util.SimpleBudget
hasNext() - Method in class moa.recommender.rc.data.impl.MemRecommenderData.RatingIterator
hasNext() - Method in class moa.recommender.rc.utils.DenseVector.DenseVectorIterator
hasNext() - Method in class moa.recommender.rc.utils.SparseVector.SparseVectorIterator
hasNoiseClass() - Method in class moa.evaluation.MembershipMatrix
HDDM_A_Test - Class in moa.classifiers.core.driftdetection: Online drift detection method based on Hoeffding's bounds.
HDDM_A_Test() - Constructor for class moa.classifiers.core.driftdetection.HDDM_A_Test
HDDM_W_Test - Class in moa.classifiers.core.driftdetection: Online drift detection method based on McDiarmid's bounds.
HDDM_W_Test() - Constructor for class moa.classifiers.core.driftdetection.HDDM_W_Test
HDDM_W_Test.SampleInfo - Class in moa.classifiers.core.driftdetection
HDDM_W_Test.SampleInfo() - Constructor for class moa.classifiers.core.driftdetection.HDDM_W_Test.SampleInfo
header - Variable in class moa.classifiers.meta.TemporallyAugmentedClassifier
headerToString() - Method in class moa.evaluation.LearningCurve
helpButton - Variable in class moa.gui.OptionsConfigurationPanel
hFunctions - Static variable in class moa.streams.generators.WaveformGenerator
highlight(boolean) - Method in class moa.gui.visualization.ClusterPanel
highlight(boolean) - Method in class moa.gui.visualization.OutlierPanel
highlight(boolean) - Method in class moa.gui.visualization.PointPanel
highligted - Variable in class moa.gui.visualization.ClusterPanel
highligted - Variable in class moa.gui.visualization.OutlierPanel
highligted - Variable in class moa.gui.visualization.PointPanel
HINGE - Static variable in class moa.classifiers.functions.SGD
HINGE - Static variable in class moa.classifiers.functions.SGDMultiClass
HINGE - Static variable in class moa.classifiers.functions.SPegasos
hitEndOfFile - Variable in class moa.streams.ArffFileStream
hitEndOfFile - Variable in class moa.streams.clustering.FileStream
HoeffdingAdaptiveTree - Class in moa.classifiers.trees: Hoeffding Adaptive Tree for evolving data streams.
HoeffdingAdaptiveTree() - Constructor for class moa.classifiers.trees.HoeffdingAdaptiveTree
HoeffdingAdaptiveTree.AdaLearningNode - Class in moa.classifiers.trees
HoeffdingAdaptiveTree.AdaLearningNode(double[]) - Constructor for class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaLearningNode
HoeffdingAdaptiveTree.AdaSplitNode - Class in moa.classifiers.trees
HoeffdingAdaptiveTree.AdaSplitNode(InstanceConditionalTest, double[], int) - Constructor for class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaSplitNode
HoeffdingAdaptiveTree.AdaSplitNode(InstanceConditionalTest, double[]) - Constructor for class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaSplitNode
HoeffdingAdaptiveTree.NewNode - Interface in moa.classifiers.trees
HoeffdingOptionTree - Class in moa.classifiers.trees: Hoeffding Option Tree.
HoeffdingOptionTree() - Constructor for class moa.classifiers.trees.HoeffdingOptionTree
HoeffdingOptionTree.ActiveLearningNode - Class in moa.classifiers.trees
HoeffdingOptionTree.ActiveLearningNode(double[]) - Constructor for class moa.classifiers.trees.HoeffdingOptionTree.ActiveLearningNode
HoeffdingOptionTree.FoundNode - Class in moa.classifiers.trees
HoeffdingOptionTree.FoundNode(HoeffdingOptionTree.Node, HoeffdingOptionTree.SplitNode, int) - Constructor for class moa.classifiers.trees.HoeffdingOptionTree.FoundNode
HoeffdingOptionTree.InactiveLearningNode - Class in moa.classifiers.trees
HoeffdingOptionTree.InactiveLearningNode(double[]) - Constructor for class moa.classifiers.trees.HoeffdingOptionTree.InactiveLearningNode
HoeffdingOptionTree.LearningNode - Class in moa.classifiers.trees
HoeffdingOptionTree.LearningNode(double[]) - Constructor for class moa.classifiers.trees.HoeffdingOptionTree.LearningNode
HoeffdingOptionTree.LearningNodeNB - Class in moa.classifiers.trees
HoeffdingOptionTree.LearningNodeNB(double[]) - Constructor for class moa.classifiers.trees.HoeffdingOptionTree.LearningNodeNB
HoeffdingOptionTree.LearningNodeNBAdaptive - Class in moa.classifiers.trees
HoeffdingOptionTree.LearningNodeNBAdaptive(double[]) - Constructor for class moa.classifiers.trees.HoeffdingOptionTree.LearningNodeNBAdaptive
HoeffdingOptionTree.Node - Class in moa.classifiers.trees
HoeffdingOptionTree.Node(double[]) - Constructor for class moa.classifiers.trees.HoeffdingOptionTree.Node
HoeffdingOptionTree.SplitNode - Class in moa.classifiers.trees
HoeffdingOptionTree.SplitNode(InstanceConditionalTest, double[]) - Constructor for class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
HoeffdingTree - Class in moa.classifiers.trees: Hoeffding Tree or VFDT.
HoeffdingTree() - Constructor for class moa.classifiers.trees.HoeffdingTree
HoeffdingTree.ActiveLearningNode - Class in moa.classifiers.trees
HoeffdingTree.ActiveLearningNode(double[]) - Constructor for class moa.classifiers.trees.HoeffdingTree.ActiveLearningNode
HoeffdingTree.FoundNode - Class in moa.classifiers.trees
HoeffdingTree.FoundNode(HoeffdingTree.Node, HoeffdingTree.SplitNode, int) - Constructor for class moa.classifiers.trees.HoeffdingTree.FoundNode
HoeffdingTree.InactiveLearningNode - Class in moa.classifiers.trees
HoeffdingTree.InactiveLearningNode(double[]) - Constructor for class moa.classifiers.trees.HoeffdingTree.InactiveLearningNode
HoeffdingTree.LearningNode - Class in moa.classifiers.trees
HoeffdingTree.LearningNode(double[]) - Constructor for class moa.classifiers.trees.HoeffdingTree.LearningNode
HoeffdingTree.LearningNodeNB - Class in moa.classifiers.trees
HoeffdingTree.LearningNodeNB(double[]) - Constructor for class moa.classifiers.trees.HoeffdingTree.LearningNodeNB
HoeffdingTree.LearningNodeNBAdaptive - Class in moa.classifiers.trees
HoeffdingTree.LearningNodeNBAdaptive(double[]) - Constructor for class moa.classifiers.trees.HoeffdingTree.LearningNodeNBAdaptive
HoeffdingTree.Node - Class in moa.classifiers.trees
HoeffdingTree.Node(double[]) - Constructor for class moa.classifiers.trees.HoeffdingTree.Node
HoeffdingTree.SplitNode - Class in moa.classifiers.trees
HoeffdingTree.SplitNode(InstanceConditionalTest, double[], int) - Constructor for class moa.classifiers.trees.HoeffdingTree.SplitNode
HoeffdingTree.SplitNode(InstanceConditionalTest, double[]) - Constructor for class moa.classifiers.trees.HoeffdingTree.SplitNode
HoeffdingTreeClassifLeaves - Class in moa.classifiers.multilabel: Hoeffding Tree that have a classifier at the leaves.
HoeffdingTreeClassifLeaves() - Constructor for class moa.classifiers.multilabel.HoeffdingTreeClassifLeaves
HoeffdingTreeClassifLeaves.LearningNodeClassifier - Class in moa.classifiers.multilabel
HoeffdingTreeClassifLeaves.LearningNodeClassifier(double[]) - Constructor for class moa.classifiers.multilabel.HoeffdingTreeClassifLeaves.LearningNodeClassifier
HoeffdingTreeClassifLeaves.LearningNodeClassifier(double[], Classifier, HoeffdingTreeClassifLeaves) - Constructor for class moa.classifiers.multilabel.HoeffdingTreeClassifLeaves.LearningNodeClassifier
horizonOption - Variable in class moa.clusterers.clustree.ClusTree
horizonOption - Variable in class moa.clusterers.denstream.WithDBSCAN
horizonOption - Variable in class moa.clusterers.WekaClusteringAlgorithm
HyperplaneGenerator - Class in moa.streams.generators: Stream generator for Hyperplane data stream.
HyperplaneGenerator() - Constructor for class moa.streams.generators.HyperplaneGenerator

I

id - Variable in class moa.classifiers.rules.core.Rule.Builder
id(int) - Method in class moa.classifiers.rules.core.Rule.Builder
ID - Variable in class moa.classifiers.trees.FIMTDD.Node
ID - Variable in class moa.classifiers.trees.ORTO.Node
id - Variable in class moa.clusterers.outliers.AbstractC.ISBIndex.ISBNode
id - Variable in class moa.clusterers.outliers.Angiulli.ISBIndex.ISBNode
id - Variable in class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
id - Variable in class moa.clusterers.outliers.MyBaseOutlierDetector.Outlier
id - Variable in class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBNode
IDenseMacroCluster - Interface in moa.clusterers.macro
illegalNameCharacters - Static variable in class moa.options.AbstractOption: Array of characters not valid to use in option names.
IMacroClusterer - Interface in moa.clusterers.macro
iMaxMemUsage - Variable in class moa.clusterers.outliers.MyBaseOutlierDetector
implementsMicroClusterer() - Method in class moa.clusterers.AbstractClusterer
implementsMicroClusterer() - Method in interface moa.clusterers.Clusterer
implementsMicroClusterer() - Method in class moa.clusterers.ClusterGenerator
implementsMicroClusterer() - Method in class moa.clusterers.clustream.Clustream
implementsMicroClusterer() - Method in class moa.clusterers.clustream.WithKmeans: Miscellaneous
implementsMicroClusterer() - Method in class moa.clusterers.clustree.ClusTree
implementsMicroClusterer() - Method in class moa.clusterers.denstream.WithDBSCAN
implementsMicroClusterer() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
improveObjectOnce(int) - Method in class moa.clusterers.outliers.AnyOut.AnyOutCore
inactiveLeafByteSizeEstimate - Variable in class moa.classifiers.trees.HoeffdingOptionTree
inactiveLeafByteSizeEstimate - Variable in class moa.classifiers.trees.HoeffdingTree
inactiveLeafByteSizeEstimate - Variable in class moa.classifiers.trees.ORTO
inactiveLeafNodeCount - Variable in class moa.classifiers.trees.HoeffdingOptionTree
inactiveLeafNodeCount - Variable in class moa.classifiers.trees.HoeffdingTree
incrCutPoint - Variable in class moa.classifiers.core.driftdetection.HDDM_W_Test
increase() - Method in class moa.clusterers.denstream.Timestamp
incrementValueOption - Variable in class moa.tasks.RunStreamTasks
incrementValueOption - Variable in class moa.tasks.RunTasks
independentBoundedConditionSum - Variable in class moa.classifiers.core.driftdetection.HDDM_W_Test.SampleInfo
index - Variable in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.MyHeapElement: the index of this element.
index - Variable in class moa.classifiers.meta.ADACC: Current stability index
indexCache - Variable in class moa.streams.filters.CacheFilter
InfoGainSplitCriterion - Class in moa.classifiers.core.splitcriteria: Class for computing splitting criteria using information gain with respect to distributions of class values.
InfoGainSplitCriterion() - Constructor for class moa.classifiers.core.splitcriteria.InfoGainSplitCriterion
InfoGainSplitCriterionMultilabel - Class in moa.classifiers.core.splitcriteria: Class for computing splitting criteria using information gain with respect to distributions of class values for Multilabel data.
InfoGainSplitCriterionMultilabel() - Constructor for class moa.classifiers.core.splitcriteria.InfoGainSplitCriterionMultilabel
InfoPanel - Class in moa.gui.visualization
InfoPanel(JFrame) - Constructor for class moa.gui.visualization.InfoPanel: Creates new form InfoPanel
Init() - Method in class moa.clusterers.outliers.AbstractC.AbstractC
Init() - Method in class moa.clusterers.outliers.Angiulli.ApproxSTORM
Init() - Method in class moa.clusterers.outliers.Angiulli.ExactSTORM
Init() - Method in class moa.clusterers.outliers.AnyOut.AnyOut
Init() - Method in class moa.clusterers.outliers.MCOD.MCOD
Init() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
Init() - Method in class moa.clusterers.outliers.SimpleCOD.SimpleCOD
init() - Method in class moa.recommender.dataset.impl.FlixsterDataset
init() - Method in class moa.recommender.dataset.impl.JesterDataset
init() - Method in class moa.recommender.dataset.impl.MovielensDataset
init() - Method in class moa.streams.filters.CacheFilter
initClassifiers - Variable in class moa.classifiers.meta.LimAttClassifier
initHeader(Instances) - Method in class moa.classifiers.meta.TemporallyAugmentedClassifier
initialDBScan() - Method in class moa.clusterers.denstream.WithDBSCAN
initialisePerceptron - Variable in class moa.classifiers.rules.functions.Perceptron
initialize() - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: initializes the ranges and the attributes being used.
initialize(RuleActiveLearningNode) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
initialize(RuleActiveLearningNode) - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
initializeAlternateTree(FIMTDD) - Method in class moa.classifiers.trees.FIMTDD.SplitNode
initializeAttributeIndices() - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: initializes the attribute indices.
initialized - Variable in class moa.clusterers.streamkm.StreamKM
initializeEntry(Entry, long) - Method in class moa.clusterers.clustree.Entry: When this entry is empty, give it it's first values.
initializeRanges() - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Initializes the ranges using all instances of the dataset.
initializeRanges(int[]) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Initializes the ranges of a subset of the instances of this dataset.
initializeRanges(int[], int, int) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Initializes the ranges of a subset of the instances of this dataset.
initializeRangesEmpty(int, double[][]) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Used to initialize the ranges.
initializeRuleStatistics(RuleClassification, Predicates, Instance) - Method in class moa.classifiers.rules.RuleClassifier
initialNumInstancesOption - Variable in class moa.classifiers.meta.LimAttClassifier
initialPauseInterval - Static variable in class moa.gui.visualization.RunOutlierVisualizer: the pause interval, being read from the gui at startup
initialPauseInterval - Static variable in class moa.gui.visualization.RunVisualizer: the pause interval, being read from the gui at startup
initKernels() - Method in class moa.streams.clustering.RandomRBFGeneratorEvents
initKm1 - Variable in class moa.classifiers.meta.OzaBoostAdwin
initLearnRate - Variable in class moa.classifiers.trees.ORTO
initMatrixCodes - Variable in class moa.classifiers.meta.LeveragingBag
initMatrixCodes - Variable in class moa.classifiers.meta.LimAttClassifier
initMatrixCodes - Variable in class moa.classifiers.meta.OzaBoostAdwin
InitNode() - Method in class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
initObject(int, double[]) - Method in class moa.clusterers.outliers.AnyOut.AnyOutCore
initPointsOption - Variable in class moa.clusterers.denstream.WithDBSCAN
initVariables() - Method in class moa.classifiers.meta.ADACC
initVariables() - Method in class moa.classifiers.meta.DACC: Initializes the method variables
initVisualEvalPanel() - Method in class moa.gui.TaskTextViewerPanel
INMEM_PREFIX_STRING - Static variable in class moa.options.AbstractClassOption: The prefix text to use to indicate inmem.
input(double) - Method in class moa.classifiers.core.driftdetection.AbstractChangeDetector: Adding a numeric value to the change detector

The output of the change detector is modified after the insertion of a new item inside.
input(double) - Method in class moa.classifiers.core.driftdetection.ADWINChangeDetector
input(double) - Method in interface moa.classifiers.core.driftdetection.ChangeDetector: Adding a numeric value to the change detector

The output of the change detector is modified after the insertion of a new item inside.
input(double) - Method in class moa.classifiers.core.driftdetection.CusumDM
input(double) - Method in class moa.classifiers.core.driftdetection.DDM
input(double) - Method in class moa.classifiers.core.driftdetection.EDDM
input(double) - Method in class moa.classifiers.core.driftdetection.EnsembleDriftDetectionMethods
input(double) - Method in class moa.classifiers.core.driftdetection.EWMAChartDM
input(double) - Method in class moa.classifiers.core.driftdetection.GeometricMovingAverageDM
input(double) - Method in class moa.classifiers.core.driftdetection.HDDM_A_Test
input(boolean) - Method in class moa.classifiers.core.driftdetection.HDDM_W_Test
input(double) - Method in class moa.classifiers.core.driftdetection.HDDM_W_Test
input(double) - Method in class moa.classifiers.core.driftdetection.PageHinkleyDM
input(double) - Method in class moa.classifiers.core.driftdetection.SeqDrift1ChangeDetector
input(double) - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector
inputByteSize - Variable in class moa.core.InputStreamProgressMonitor: The number of bytes to read in total
inputBytesRead - Variable in class moa.core.InputStreamProgressMonitor: The number of bytes read so far
inputFilesOption - Variable in class moa.tasks.Plot: Comma separated list of input *csv files.
inputInstance - Variable in class moa.streams.ConceptDriftRealStream
inputStream - Variable in class moa.streams.ConceptDriftRealStream
inputStream - Variable in class moa.streams.ConceptDriftStream
inputStream - Variable in class moa.streams.filters.AbstractStreamFilter: The input stream to this filter.
InputStreamProgressMonitor - Class in moa.core: Class for monitoring the progress of reading an input stream.
InputStreamProgressMonitor(InputStream) - Constructor for class moa.core.InputStreamProgressMonitor
inputValues - Variable in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
inRanges(Instance, double[][]) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Test if an instance is within the given ranges.
insert(Instance, long) - Method in class moa.clusterers.clustream.ClustreamKernel
insert(ClusKernel, Budget, long) - Method in class moa.clusterers.clustree.ClusTree: Insert a new point in the Tree.
insert(Instance, long) - Method in class moa.clusterers.denstream.MicroCluster
insert(CFCluster) - Method in class moa.clusterers.macro.NonConvexCluster
Insert(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.AbstractC.ISBIndex
Insert(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.Angiulli.ISBIndex
Insert(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.MCOD.ISBIndex
Insert(ISBIndex.ISBNode, Long) - Method in class moa.clusterers.outliers.MCOD.MCODBase.EventQueue
Insert(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.SimpleCOD.ISBIndex
Insert(ISBIndex.ISBNode, Long) - Method in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase.EventQueue
insert(double) - Method in class moa.core.GreenwaldKhannaQuantileSummary
insertEntry(LearningEvaluation) - Method in class moa.evaluation.LearningCurve
insertSorted(double, Instance) - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborList: Inserts an instance neighbor into the list, maintaining the list sorted by distance.
insertTuple(GreenwaldKhannaQuantileSummary.Tuple, int) - Method in class moa.core.GreenwaldKhannaQuantileSummary
insertValue(double, int, double) - Method in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserver.Node
insertValue(double, double) - Method in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserverRegression.Node
insertValue(double, double, double) - Method in class moa.classifiers.core.attributeclassobservers.FIMTDDNumericAttributeClassObserver.Node: Insert a new value into the tree, updating both the sum of values and sum of squared values arrays
insertValue(double, double, double) - Method in class moa.classifiers.rules.core.attributeclassobservers.FIMTDDNumericAttributeClassLimitObserver.Node: Insert a new value into the tree, updating both the sum of values and sum of squared values arrays
inst - Variable in class moa.clusterers.outliers.AbstractC.ISBIndex.ISBNode
inst - Variable in class moa.clusterers.outliers.Angiulli.ISBIndex.ISBNode
inst - Variable in class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
inst - Variable in class moa.clusterers.outliers.MyBaseOutlierDetector.Outlier
inst - Variable in class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBNode
instance - Variable in class moa.classifiers.rules.RuleClassifier
instanceChildIndex(Instance) - Method in class moa.classifiers.trees.FIMTDD.SplitNode
instanceChildIndex(Instance) - Method in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
instanceChildIndex(Instance) - Method in class moa.classifiers.trees.HoeffdingTree.SplitNode
instanceChildIndex(Instance) - Method in class moa.classifiers.trees.ORTO.SplitNode
InstanceConditionalBinaryTest - Class in moa.classifiers.core.conditionaltests: Abstract binary conditional test for instances to use to split nodes in Hoeffding trees.
InstanceConditionalBinaryTest() - Constructor for class moa.classifiers.core.conditionaltests.InstanceConditionalBinaryTest
InstanceConditionalTest - Class in moa.classifiers.core.conditionaltests: Abstract conditional test for instances to use to split nodes in Hoeffding trees.
InstanceConditionalTest() - Constructor for class moa.classifiers.core.conditionaltests.InstanceConditionalTest
instanceLimitOption - Variable in class moa.tasks.EvaluateClustering
instanceLimitOption - Variable in class moa.tasks.EvaluateConceptDrift
instanceLimitOption - Variable in class moa.tasks.EvaluateInterleavedChunks: Allows to define the maximum number of instances to test/train on (-1 = no limit).
instanceLimitOption - Variable in class moa.tasks.EvaluateInterleavedTestThenTrain
instanceLimitOption - Variable in class moa.tasks.EvaluatePrequential
instanceLimitOption - Variable in class moa.tasks.EvaluatePrequentialRegression
instanceRandom - Variable in class moa.streams.clustering.RandomRBFGeneratorEvents
instanceRandom - Variable in class moa.streams.generators.AgrawalGenerator
instanceRandom - Variable in class moa.streams.generators.cd.AbstractConceptDriftGenerator
instanceRandom - Variable in class moa.streams.generators.HyperplaneGenerator
instanceRandom - Variable in class moa.streams.generators.LEDGenerator
instanceRandom - Variable in class moa.streams.generators.RandomRBFGenerator
instanceRandom - Variable in class moa.streams.generators.RandomTreeGenerator
instanceRandom - Variable in class moa.streams.generators.SEAGenerator
instanceRandom - Variable in class moa.streams.generators.STAGGERGenerator
instanceRandom - Variable in class moa.streams.generators.WaveformGenerator
instanceRandomSeedOption - Variable in class moa.streams.clustering.RandomRBFGeneratorEvents
instanceRandomSeedOption - Variable in class moa.streams.generators.AgrawalGenerator
instanceRandomSeedOption - Variable in class moa.streams.generators.cd.AbstractConceptDriftGenerator
instanceRandomSeedOption - Variable in class moa.streams.generators.HyperplaneGenerator
instanceRandomSeedOption - Variable in class moa.streams.generators.LEDGenerator
instanceRandomSeedOption - Variable in class moa.streams.generators.RandomRBFGenerator
instanceRandomSeedOption - Variable in class moa.streams.generators.RandomTreeGenerator
instanceRandomSeedOption - Variable in class moa.streams.generators.SEAGenerator
instanceRandomSeedOption - Variable in class moa.streams.generators.STAGGERGenerator
instanceRandomSeedOption - Variable in class moa.streams.generators.WaveformGenerator
instances - Variable in class moa.streams.ArffFileStream
instances - Variable in class moa.streams.clustering.FileStream
INSTANCES_BETWEEN_MONITOR_UPDATES - Static variable in class moa.tasks.MainTask: The number of instances between monitor updates.
instancesBuffer - Variable in class moa.classifiers.meta.WEKAClassifier
InstancesHeader - Class in moa.core: Class for storing the header or context of a data stream.
InstancesHeader(Instances) - Constructor for class moa.core.InstancesHeader
instancesSeen - Variable in class moa.classifiers.rules.driftdetection.PageHinkleyFading
instancesSeen - Variable in class moa.classifiers.rules.RuleClassification
instancesSeen - Variable in class moa.classifiers.trees.FIMTDD.FIMTDDPerceptron
instancesSeen - Variable in class moa.classifiers.trees.ORTO.ORTOPerceptron
instancesSeenTest - Variable in class moa.classifiers.rules.RuleClassification
InstanceStream - Interface in moa.streams: Interface representing a data stream of instances.
INT_ADD - Static variable in class moa.clusterers.clustree.util.SimpleBudget
INT_DIV - Static variable in class moa.clusterers.clustree.util.SimpleBudget
INT_MULT - Static variable in class moa.clusterers.clustree.util.SimpleBudget
integerAddition() - Method in interface moa.clusterers.clustree.util.Budget: Inform the Budget class that an integer addition has been performed by the tree.
integerAddition(int) - Method in interface moa.clusterers.clustree.util.Budget: Inform the Budget that a certain number of integer additions have been done.
integerAddition() - Method in class moa.clusterers.clustree.util.SimpleBudget
integerAddition(int) - Method in class moa.clusterers.clustree.util.SimpleBudget
integerDivision() - Method in interface moa.clusterers.clustree.util.Budget: Inform the Budget class that a integer division has been performed by the tree.
integerDivision(int) - Method in interface moa.clusterers.clustree.util.Budget: Inform the Budget that a certain number of integer divisions have been performed.
integerDivision() - Method in class moa.clusterers.clustree.util.SimpleBudget
integerDivision(int) - Method in class moa.clusterers.clustree.util.SimpleBudget
integerMultiplication() - Method in interface moa.clusterers.clustree.util.Budget: Inform the Budget class that a integer multiplicaton has been performed by the tree.
integerMultiplication(int) - Method in interface moa.clusterers.clustree.util.Budget: Inform the Budget that a certain number of integer multiplications have been performed.
integerMultiplication() - Method in class moa.clusterers.clustree.util.SimpleBudget
integerMultiplication(int) - Method in class moa.clusterers.clustree.util.SimpleBudget
IntOption - Class in moa.options: Int option.
IntOption(String, char, String, int) - Constructor for class moa.options.IntOption
IntOption(String, char, String, int, int, int) - Constructor for class moa.options.IntOption
IntOptionEditComponent - Class in moa.gui: An OptionEditComponent that lets the user edit an integer option.
IntOptionEditComponent(IntOption) - Constructor for class moa.gui.IntOptionEditComponent
intToCLIString(int) - Static method in class moa.options.IntOption
invalidate() - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: invalidates all initializations.
inverseError(double) - Static method in class moa.clusterers.clustream.ClustreamKernel: Approximates the inverse error function.
InverseErrorWeightedVote - Class in moa.classifiers.rules.core.voting: InverseErrorWeightedVote class for weighted votes based on estimates of errors.
InverseErrorWeightedVote() - Constructor for class moa.classifiers.rules.core.voting.InverseErrorWeightedVote
invertSelectionTipText() - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Returns the tip text for this property.
isALeaf() - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNode: Checks if node is a leaf.
isAnomaly(Instance, double, double, int) - Method in class moa.classifiers.rules.core.Rule
isAnomaly(Instance, double, double, int) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
isAnomaly(Instance, double, double, int) - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
ISB - Variable in class moa.clusterers.outliers.AbstractC.AbstractCBase
ISB - Variable in class moa.clusterers.outliers.Angiulli.STORMBase
ISB - Variable in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
ISB_PD - Variable in class moa.clusterers.outliers.MCOD.MCODBase
ISBIndex - Class in moa.clusterers.outliers.AbstractC
ISBIndex(double, double) - Constructor for class moa.clusterers.outliers.AbstractC.ISBIndex
ISBIndex - Class in moa.clusterers.outliers.Angiulli
ISBIndex(double, int) - Constructor for class moa.clusterers.outliers.Angiulli.ISBIndex
ISBIndex - Class in moa.clusterers.outliers.MCOD
ISBIndex(double, int) - Constructor for class moa.clusterers.outliers.MCOD.ISBIndex
ISBIndex - Class in moa.clusterers.outliers.SimpleCOD
ISBIndex(double, int) - Constructor for class moa.clusterers.outliers.SimpleCOD.ISBIndex
ISBIndex.ISBNode - Class in moa.clusterers.outliers.AbstractC
ISBIndex.ISBNode(Instance, StreamObj, Long) - Constructor for class moa.clusterers.outliers.AbstractC.ISBIndex.ISBNode
ISBIndex.ISBNode - Class in moa.clusterers.outliers.Angiulli
ISBIndex.ISBNode(Instance, StreamObj, Long) - Constructor for class moa.clusterers.outliers.Angiulli.ISBIndex.ISBNode
ISBIndex.ISBNode - Class in moa.clusterers.outliers.MCOD
ISBIndex.ISBNode(Instance, StreamObj, Long) - Constructor for class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
ISBIndex.ISBNode - Class in moa.clusterers.outliers.SimpleCOD
ISBIndex.ISBNode(Instance, StreamObj, Long) - Constructor for class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBNode
ISBIndex.ISBNode.NodeType - Enum in moa.clusterers.outliers.MCOD
ISBIndex.ISBSearchResult - Class in moa.clusterers.outliers.AbstractC
ISBIndex.ISBSearchResult(ISBIndex.ISBNode, double) - Constructor for class moa.clusterers.outliers.AbstractC.ISBIndex.ISBSearchResult
ISBIndex.ISBSearchResult - Class in moa.clusterers.outliers.Angiulli
ISBIndex.ISBSearchResult(ISBIndex.ISBNode, double) - Constructor for class moa.clusterers.outliers.Angiulli.ISBIndex.ISBSearchResult
ISBIndex.ISBSearchResult - Class in moa.clusterers.outliers.MCOD
ISBIndex.ISBSearchResult(ISBIndex.ISBNode, double) - Constructor for class moa.clusterers.outliers.MCOD.ISBIndex.ISBSearchResult
ISBIndex.ISBSearchResult - Class in moa.clusterers.outliers.SimpleCOD
ISBIndex.ISBSearchResult(ISBIndex.ISBNode, double) - Constructor for class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBSearchResult
isBufferStoring - Variable in class moa.classifiers.meta.WEKAClassifier
isCancelled() - Method in class moa.tasks.NullMonitor
isCancelled() - Method in class moa.tasks.StandardTaskMonitor
isCancelled() - Method in interface moa.tasks.TaskMonitor: Gets whether the task monitored is cancelled.
isCellEditable(int, int) - Method in class moa.gui.conceptdrift.CDTaskManagerPanel.TaskTableModel
isCellEditable(int, int) - Method in class moa.gui.LineGraphViewPanel.PlotTableModel
isCellEditable(int, int) - Method in class moa.gui.RegressionTaskManagerPanel.TaskTableModel
isCellEditable(int, int) - Method in class moa.gui.TaskManagerPanel.TaskTableModel
isChangeDetected - Variable in class moa.classifiers.core.driftdetection.AbstractChangeDetector: Change was detected
isClassificationEnabled - Variable in class moa.classifiers.meta.WEKAClassifier
isClustered() - Method in class moa.clusterers.macro.dbscan.DenseMicroCluster
isComplete - Variable in class moa.tasks.StandardTaskMonitor
isComplete() - Method in class moa.tasks.TaskThread
isCovering(Instance) - Method in class moa.classifiers.rules.core.Rule
isEmpty() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborList: Gets whether the list is empty.
isEmpty() - Method in class moa.clusterers.clustream.ClustreamKernel: Check if this cluster is empty or not.
isEmpty() - Method in class moa.clusterers.clustree.ClusKernel: Check if this cluster is empty or not.
isEmpty() - Method in class moa.clusterers.clustree.Entry: Check if this Entry is empty or not.
isEnabled(int) - Method in class moa.evaluation.MeasureCollection
isEnabledDrawClustering() - Method in class moa.gui.clustertab.ClusteringVisualTab
isEnabledDrawGroundTruth() - Method in class moa.gui.clustertab.ClusteringVisualTab
isEnabledDrawMicroclustering() - Method in class moa.gui.clustertab.ClusteringVisualTab
isEnabledDrawOutliers() - Method in class moa.gui.outliertab.OutlierVisualTab
isEnabledDrawPoints() - Method in class moa.gui.clustertab.ClusteringVisualTab
isEnabledDrawPoints() - Method in class moa.gui.outliertab.OutlierVisualTab
isEqual(NumericAttributeBinaryRulePredicate) - Method in class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
isGroundTruth() - Method in class moa.cluster.Cluster
isIncludedInRuleNode(NumericAttributeBinaryRulePredicate) - Method in class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
isInitialized - Variable in class moa.classifiers.core.driftdetection.AbstractChangeDetector: The change detector has been initialized with the option values
isInitialized - Variable in class moa.classifiers.trees.HoeffdingTree.ActiveLearningNode
isInitialized - Variable in class moa.streams.filters.CacheFilter
isIrrelevant(double) - Method in class moa.clusterers.clustree.Entry: Returns true if this entry is irrelevant with respecto the given threshold.
isJavaVersionOK() - Static method in class moa.DoTask: Checks if the Java version is recent enough to run MOA.
isLeaf() - Method in class moa.classifiers.trees.FIMTDD.Node
isLeaf() - Method in class moa.classifiers.trees.HoeffdingOptionTree.Node
isLeaf() - Method in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
isLeaf() - Method in class moa.classifiers.trees.HoeffdingTree.Node
isLeaf() - Method in class moa.classifiers.trees.HoeffdingTree.SplitNode
isLeaf() - Method in class moa.classifiers.trees.ORTO.Node
isLeaf() - Method in class moa.classifiers.trees.ORTO.OptionNode
isLeaf() - Method in class moa.classifiers.trees.ORTO.SplitNode
isLeaf() - Method in class moa.clusterers.clustree.Node: Checks if this node is a leaf.
isMissingValue(double) - Static method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Tests if the given value codes "missing".
IsNodeIdInWin(long) - Method in class moa.clusterers.outliers.AbstractC.AbstractCBase
IsNodeIdInWin(long) - Method in class moa.clusterers.outliers.Angiulli.STORMBase
IsNodeIdInWin(long) - Method in class moa.clusterers.outliers.AnyOut.AnyOut
IsNodeIdInWin(long) - Method in class moa.clusterers.outliers.MCOD.MCODBase
IsNodeIdInWin(long) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
IsNodeIdInWin(long) - Method in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
isNoise() - Method in class moa.gui.visualization.DataPoint
isNullError() - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaLearningNode
isNullError() - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaSplitNode
isNullError() - Method in interface moa.classifiers.trees.HoeffdingAdaptiveTree.NewNode
isOutiler() - Method in class moa.clusterers.outliers.AnyOut.util.DataObject
isOutlier(int) - Method in class moa.clusterers.outliers.AnyOut.AnyOutCore
isOutputFile - Variable in class moa.options.FileOption
isOutputFile() - Method in class moa.options.FileOption
isPaintable() - Method in class weka.gui.MOAClassOptionEditor: Returns true since this editor is paintable.
isPaused() - Method in class moa.tasks.NullMonitor
isPaused() - Method in class moa.tasks.StandardTaskMonitor
isPaused() - Method in interface moa.tasks.TaskMonitor: Gets whether the task monitored is paused.
isPresent() - Static method in class moa.core.SizeOf: Checks whteher the agent is present.
isPublicConcreteClassOfType(String, Class<?>) - Static method in class moa.core.AutoClassDiscovery
isRandomizable() - Method in class moa.classifiers.active.ActiveClassifier
isRandomizable() - Method in class moa.classifiers.bayes.NaiveBayes
isRandomizable() - Method in class moa.classifiers.bayes.NaiveBayesMultinomial
isRandomizable() - Method in interface moa.classifiers.Classifier: Gets whether this classifier needs a random seed.
isRandomizable() - Method in class moa.classifiers.drift.DriftDetectionMethodClassifier
isRandomizable() - Method in class moa.classifiers.functions.MajorityClass
isRandomizable() - Method in class moa.classifiers.functions.NoChange
isRandomizable() - Method in class moa.classifiers.functions.Perceptron
isRandomizable() - Method in class moa.classifiers.functions.SGD
isRandomizable() - Method in class moa.classifiers.functions.SGDMultiClass
isRandomizable() - Method in class moa.classifiers.functions.SPegasos
isRandomizable() - Method in class moa.classifiers.lazy.kNN
isRandomizable() - Method in class moa.classifiers.lazy.kNNwithPAW
isRandomizable() - Method in class moa.classifiers.lazy.kNNwithPAWandADWIN
isRandomizable() - Method in class moa.classifiers.meta.AccuracyUpdatedEnsemble: Determines whether the classifier is randomizable.
isRandomizable() - Method in class moa.classifiers.meta.AccuracyWeightedEnsemble: Determines whether the classifier is randomizable.
isRandomizable() - Method in class moa.classifiers.meta.DACC
isRandomizable() - Method in class moa.classifiers.meta.LeveragingBag
isRandomizable() - Method in class moa.classifiers.meta.LimAttClassifier
isRandomizable() - Method in class moa.classifiers.meta.OCBoost
isRandomizable() - Method in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble: Determines whether the classifier is randomizable.
isRandomizable() - Method in class moa.classifiers.meta.OnlineSmoothBoost
isRandomizable() - Method in class moa.classifiers.meta.OzaBag
isRandomizable() - Method in class moa.classifiers.meta.OzaBagAdwin
isRandomizable() - Method in class moa.classifiers.meta.OzaBoost
isRandomizable() - Method in class moa.classifiers.meta.OzaBoostAdwin
isRandomizable() - Method in class moa.classifiers.meta.RandomRules
isRandomizable() - Method in class moa.classifiers.meta.TemporallyAugmentedClassifier
isRandomizable() - Method in class moa.classifiers.meta.WeightedMajorityAlgorithm
isRandomizable() - Method in class moa.classifiers.meta.WEKAClassifier
isRandomizable() - Method in class moa.classifiers.multilabel.MajorityLabelset
isRandomizable() - Method in class moa.classifiers.multilabel.meta.MLOzaBag
isRandomizable() - Method in class moa.classifiers.rules.AbstractAMRules: description of the Methods used.
isRandomizable() - Method in class moa.classifiers.rules.AMRulesRegressor
isRandomizable() - Method in class moa.classifiers.rules.functions.Perceptron
isRandomizable() - Method in class moa.classifiers.rules.functions.TargetMean
isRandomizable() - Method in class moa.classifiers.rules.RuleClassifier
isRandomizable() - Method in class moa.classifiers.trees.DecisionStump
isRandomizable() - Method in class moa.classifiers.trees.FIMTDD
isRandomizable() - Method in class moa.classifiers.trees.HoeffdingOptionTree
isRandomizable() - Method in class moa.classifiers.trees.HoeffdingTree
isRandomizable() - Method in class moa.classifiers.trees.LimAttHoeffdingTree
isRandomizable() - Method in class moa.classifiers.trees.ORTO
isRandomizable() - Method in class moa.classifiers.trees.RandomHoeffdingTree
isRandomizable() - Method in interface moa.clusterers.Clusterer
isRandomizable() - Method in class moa.clusterers.ClusterGenerator
isRandomizable() - Method in class moa.clusterers.clustream.Clustream
isRandomizable() - Method in class moa.clusterers.clustream.WithKmeans
isRandomizable() - Method in class moa.clusterers.clustree.ClusTree
isRandomizable() - Method in class moa.clusterers.CobWeb
isRandomizable() - Method in class moa.clusterers.denstream.WithDBSCAN
isRandomizable() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
isRandomizable() - Method in class moa.clusterers.streamkm.StreamKM
isRandomizable() - Method in class moa.clusterers.WekaClusteringAlgorithm
isRandomizable() - Method in class moa.learners.ChangeDetectorLearner
isRegression - Variable in class moa.classifiers.meta.RandomRules
isRestartable() - Method in class moa.streams.ArffFileStream
isRestartable() - Method in class moa.streams.CachedInstancesStream
isRestartable() - Method in class moa.streams.clustering.FileStream
isRestartable() - Method in class moa.streams.clustering.RandomRBFGeneratorEvents
isRestartable() - Method in class moa.streams.ConceptDriftRealStream
isRestartable() - Method in class moa.streams.ConceptDriftStream
isRestartable() - Method in class moa.streams.FilteredStream
isRestartable() - Method in class moa.streams.filters.AbstractStreamFilter
isRestartable() - Method in class moa.streams.generators.AgrawalGenerator
isRestartable() - Method in class moa.streams.generators.cd.AbstractConceptDriftGenerator
isRestartable() - Method in class moa.streams.generators.HyperplaneGenerator
isRestartable() - Method in class moa.streams.generators.LEDGenerator
isRestartable() - Method in class moa.streams.generators.multilabel.MetaMultilabelGenerator
isRestartable() - Method in class moa.streams.generators.RandomRBFGenerator
isRestartable() - Method in class moa.streams.generators.RandomTreeGenerator
isRestartable() - Method in class moa.streams.generators.SEAGenerator
isRestartable() - Method in class moa.streams.generators.STAGGERGenerator
isRestartable() - Method in class moa.streams.generators.WaveformGenerator
isRestartable() - Method in interface moa.streams.InstanceStream: Gets whether this stream can restart.
isRestartable() - Method in class moa.streams.MultiFilteredStream
isSet - Variable in class moa.options.FlagOption
isSet() - Method in class moa.options.FlagOption
isUsingSameAttribute(NumericAttributeBinaryRulePredicate) - Method in class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
isValidCluster() - Method in class moa.gui.visualization.ClusterPanel
isValidCluster() - Method in class moa.gui.visualization.OutlierPanel
isVisited() - Method in class moa.clusterers.macro.dbscan.DenseMicroCluster
isWarningZone - Variable in class moa.classifiers.core.driftdetection.AbstractChangeDetector: Warning Zone: after a warning and before a change
isWarningZone - Variable in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
isWekaVersionOK() - Static method in class moa.DoTask: Checks if the Weka version is recent enough to run MOA.
itemExists(int) - Method in class moa.recommender.rc.data.impl.MemRecommenderData
itemExists(int) - Method in interface moa.recommender.rc.data.RecommenderData
itemFeature - Variable in class moa.recommender.rc.predictor.impl.BRISMFPredictor
itemID - Variable in class moa.recommender.rc.utils.Rating
itemsStats - Variable in class moa.recommender.rc.data.impl.MemRecommenderData
iterationControl - Variable in class moa.classifiers.active.ActiveClassifier
iterationsOption - Variable in class moa.recommender.predictor.BRISMFPredictor
iterator() - Method in class moa.clusterers.outliers.AnyOut.util.DataSet: An iterator for the set.
iterator() - Method in class moa.clusterers.outliers.utils.mtree.MTree.Query
iterator() - Method in class moa.recommender.rc.utils.DenseVector
iterator() - Method in class moa.recommender.rc.utils.SparseVector
iterator() - Method in class moa.recommender.rc.utils.Vector

J

JesterDataset - Class in moa.recommender.dataset.impl
JesterDataset() - Constructor for class moa.recommender.dataset.impl.JesterDataset
joinClustersOption - Variable in class moa.clusterers.ClusterGenerator

K

KDTree - Class in moa.classifiers.lazy.neighboursearch: Class implementing the KDTree search algorithm for nearest neighbour search.
The connection to dataset is only a reference.
KDTree() - Constructor for class moa.classifiers.lazy.neighboursearch.KDTree: Creates a new instance of KDTree.
KDTree(Instances) - Constructor for class moa.classifiers.lazy.neighboursearch.KDTree: Creates a new instance of KDTree.
KDTreeNode - Class in moa.classifiers.lazy.neighboursearch.kdtrees: A class representing a KDTree node.
KDTreeNode() - Constructor for class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNode: Constructor.
KDTreeNode(int, int, int, double[][]) - Constructor for class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNode: Constructor.
KDTreeNode(int, int, int, double[][], double[][]) - Constructor for class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNode
KDTreeNodeSplitter - Class in moa.classifiers.lazy.neighboursearch.kdtrees: Class that splits up a KDTreeNode.
KDTreeNodeSplitter() - Constructor for class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter: default constructor.
KDTreeNodeSplitter(int[], Instances, EuclideanDistance) - Constructor for class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter: Creates a new instance of KDTreeNodeSplitter.
keepClassLabel() - Method in class moa.clusterers.AbstractClusterer
keepClassLabel() - Method in interface moa.clusterers.Clusterer
keepClassLabel() - Method in class moa.clusterers.ClusterGenerator
keepClassLabel() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
keepClassLabel() - Method in class moa.clusterers.WekaClusteringAlgorithm
keepNonNumericalAttrOption - Variable in class moa.streams.clustering.FileStream
kernelRadiFactorOption - Variable in class moa.clusterers.clustream.Clustream
kernelRadiFactorOption - Variable in class moa.clusterers.clustream.WithKmeans
kernelRadiiOption - Variable in class moa.streams.clustering.RandomRBFGeneratorEvents
kernelRadiiRangeOption - Variable in class moa.streams.clustering.RandomRBFGeneratorEvents
killTreeChilds(HoeffdingAdaptiveTree) - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaLearningNode
killTreeChilds(HoeffdingAdaptiveTree) - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaSplitNode
killTreeChilds(HoeffdingAdaptiveTree) - Method in interface moa.classifiers.trees.HoeffdingAdaptiveTree.NewNode
Km1 - Variable in class moa.classifiers.meta.OzaBoostAdwin
kMeans(int, List<? extends Cluster>) - Static method in class moa.clusterers.clustream.Clustream
kMeans(int, Cluster[], List<? extends Cluster>) - Static method in class moa.clusterers.clustream.Clustream
kMeans(int, Cluster[], List<? extends Cluster>) - Static method in class moa.clusterers.clustream.WithKmeans: (The Actual Algorithm) k-means of (micro)clusters, with specified initialization points.
KMeans - Class in moa.clusterers: A kMeans implementation for microclusterings.
KMeans() - Constructor for class moa.clusterers.KMeans
kMeans(Cluster[], List<? extends Cluster>) - Static method in class moa.clusterers.KMeans: This kMeans implementation clusters a big number of microclusters into a smaller amount of macro clusters.
kMeans_gta(int, Clustering, Clustering) - Static method in class moa.clusterers.clustream.WithKmeans: k-means of (micro)clusters, with ground-truth-aided initialization.
kMeans_rand(int, Clustering) - Static method in class moa.clusterers.clustream.WithKmeans: k-means of (micro)clusters, with randomized initialization.
KMeansInpiredMethod - Class in moa.classifiers.lazy.neighboursearch.kdtrees: The class that splits a node into two such that the overall sum of squared distances of points to their centres on both sides of the (axis-parallel) splitting plane is minimum.

For more information see also:

Ashraf Masood Kibriya (2007).
KMeansInpiredMethod() - Constructor for class moa.classifiers.lazy.neighboursearch.kdtrees.KMeansInpiredMethod
kNearestNeighbours(Instance, int) - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Returns the k nearest neighbours of the supplied instance.
kNearestNeighbours(Instance, int) - Method in class moa.classifiers.lazy.neighboursearch.LinearNNSearch: Returns k nearest instances in the current neighbourhood to the supplied instance.
kNearestNeighbours(Instance, int) - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch: Returns k nearest instances in the current neighbourhood to the supplied instance.
kNN - Class in moa.classifiers.lazy: k Nearest Neighbor.
kNN() - Constructor for class moa.classifiers.lazy.kNN
knnInCluster - Variable in class moa.evaluation.CMM_GTAnalysis.CMMPoint: knn distnace within own cluster
knnIndices - Variable in class moa.evaluation.CMM_GTAnalysis.CMMPoint: knn indices (for debugging only)
kNNwithPAW - Class in moa.classifiers.lazy: k Nearest Neighbor ADAPTIVE with PAW.
kNNwithPAW() - Constructor for class moa.classifiers.lazy.kNNwithPAW
kNNwithPAWandADWIN - Class in moa.classifiers.lazy: k Nearest Neighbor ADAPTIVE with ADWIN+PAW.
kNNwithPAWandADWIN() - Constructor for class moa.classifiers.lazy.kNNwithPAWandADWIN
kOption - Variable in class moa.classifiers.lazy.kNN
kOption - Variable in class moa.clusterers.clustream.WithKmeans
kOption - Variable in class moa.clusterers.outliers.AbstractC.AbstractC
kOption - Variable in class moa.clusterers.outliers.Angiulli.ApproxSTORM
kOption - Variable in class moa.clusterers.outliers.Angiulli.ExactSTORM
kOption - Variable in class moa.clusterers.outliers.MCOD.MCOD
kOption - Variable in class moa.clusterers.outliers.SimpleCOD.SimpleCOD

L

labelCardinalityOption - Variable in class moa.streams.generators.multilabel.MetaMultilabelGenerator
labelCardinalityRatioOption - Variable in class moa.streams.generators.multilabel.MetaMultilabelGenerator
labelCardinalityVarOption - Variable in class moa.streams.generators.multilabel.MetaMultilabelGenerator
labelDelayOption - Variable in class moa.classifiers.meta.TemporallyAugmentedClassifier
labelDependencyChangeRatioOption - Variable in class moa.streams.generators.multilabel.MetaMultilabelGenerator
lambda - Variable in class moa.classifiers.core.driftdetection.HDDM_W_Test
lambdaOption - Variable in class moa.classifiers.core.driftdetection.CusumDM
lambdaOption - Variable in class moa.classifiers.core.driftdetection.EWMAChartDM
lambdaOption - Variable in class moa.classifiers.core.driftdetection.GeometricMovingAverageDM
lambdaOption - Variable in class moa.classifiers.core.driftdetection.HDDM_W_Test
lambdaOption - Variable in class moa.classifiers.core.driftdetection.PageHinkleyDM
lambdaOption - Variable in class moa.clusterers.denstream.WithDBSCAN
lambdaRegularizationOption - Variable in class moa.classifiers.functions.SGD
lambdaRegularizationOption - Variable in class moa.classifiers.functions.SGDMultiClass
lambdaRegularizationOption - Variable in class moa.classifiers.functions.SPegasos
laplaceCorrectionOption - Variable in class moa.classifiers.bayes.NaiveBayesMultinomial
lastInstanceRead - Variable in class moa.streams.ArffFileStream
lastInstanceRead - Variable in class moa.streams.clustering.FileStream
lastNominalValues - Variable in class moa.streams.filters.ReplacingMissingValuesFilter
lastSeenClass - Variable in class moa.classifiers.functions.NoChange
lastSeenClass - Variable in class moa.evaluation.WindowClassificationPerformanceEvaluator
lastTargetMean - Variable in class moa.classifiers.rules.core.Rule.Builder
lastTargetMean - Variable in class moa.classifiers.rules.nodes.RuleSplitNode
lastValueOption - Variable in class moa.tasks.RunStreamTasks
lastValueOption - Variable in class moa.tasks.RunTasks
latestPreviewChanged() - Method in class moa.gui.PreviewPanel
latestPreviewChanged() - Method in interface moa.tasks.ResultPreviewListener: This method is used to receive a signal from TaskMonitor that the lastest preview has changed.
latestPreviewGrabTime - Variable in class moa.tasks.TaskThread
latestResultPreview - Variable in class moa.tasks.StandardTaskMonitor
leafFractionOption - Variable in class moa.streams.generators.RandomTreeGenerator
leafpredictionOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree
leafpredictionOption - Variable in class moa.classifiers.trees.HoeffdingTree
learnerListOption - Variable in class moa.classifiers.meta.WeightedMajorityAlgorithm
learnerOption - Variable in class moa.classifiers.meta.AccuracyUpdatedEnsemble: Type of classifier to use as a component classifier.
learnerOption - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble: Type of classifier to use as a component classifier.
learnerOption - Variable in class moa.classifiers.meta.DACC: Base classifier
learnerOption - Variable in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble: Type of classifier to use as a component classifier.
learnerOption - Variable in class moa.classifiers.multilabel.HoeffdingTreeClassifLeaves
learnerOption - Variable in class moa.tasks.EvaluateClustering
learnerOption - Variable in class moa.tasks.EvaluateConceptDrift
learnerOption - Variable in class moa.tasks.EvaluateInterleavedChunks: Allows to select the trained classifier.
learnerOption - Variable in class moa.tasks.EvaluateInterleavedTestThenTrain
learnerOption - Variable in class moa.tasks.EvaluatePeriodicHeldOutTest
learnerOption - Variable in class moa.tasks.EvaluatePrequential
learnerOption - Variable in class moa.tasks.EvaluatePrequentialRegression
learnerOption - Variable in class moa.tasks.LearnModel
learnerOption - Variable in class moa.tasks.LearnModelRegression
learners - Variable in class moa.classifiers.meta.AccuracyUpdatedEnsemble: Ensemble classifiers.
learnFromInstance(Instance, HoeffdingTree) - Method in class moa.classifiers.multilabel.HoeffdingTreeClassifLeaves.LearningNodeClassifier
learnFromInstance(Instance, HoeffdingTree) - Method in class moa.classifiers.multilabel.MultilabelHoeffdingTree.MultilabelInactiveLearningNode
learnFromInstance(Instance, HoeffdingTree) - Method in class moa.classifiers.multilabel.MultilabelHoeffdingTree.MultilabelLearningNodeClassifier
learnFromInstance(Instance) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
learnFromInstance(Instance, HoeffdingTree) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
learnFromInstance(Instance) - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
learnFromInstance(Instance, HoeffdingOptionTree) - Method in class moa.classifiers.trees.AdaHoeffdingOptionTree.AdaLearningNode
learnFromInstance(Instance, FIMTDD, boolean) - Method in class moa.classifiers.trees.FIMTDD.LeafNode: Method to learn from an instance that passes the new instance to the perceptron learner, and also prevents the class value from being truncated to an int when it is passed to the attribute observer
learnFromInstance(Instance, HoeffdingAdaptiveTree, HoeffdingTree.SplitNode, int) - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaLearningNode
learnFromInstance(Instance, HoeffdingAdaptiveTree, HoeffdingTree.SplitNode, int) - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaSplitNode
learnFromInstance(Instance, HoeffdingAdaptiveTree, HoeffdingTree.SplitNode, int) - Method in interface moa.classifiers.trees.HoeffdingAdaptiveTree.NewNode
learnFromInstance(Instance, HoeffdingOptionTree) - Method in class moa.classifiers.trees.HoeffdingOptionTree.ActiveLearningNode
learnFromInstance(Instance, HoeffdingOptionTree) - Method in class moa.classifiers.trees.HoeffdingOptionTree.InactiveLearningNode
learnFromInstance(Instance, HoeffdingOptionTree) - Method in class moa.classifiers.trees.HoeffdingOptionTree.LearningNode
learnFromInstance(Instance, HoeffdingOptionTree) - Method in class moa.classifiers.trees.HoeffdingOptionTree.LearningNodeNBAdaptive
learnFromInstance(Instance, HoeffdingTree) - Method in class moa.classifiers.trees.HoeffdingTree.ActiveLearningNode
learnFromInstance(Instance, HoeffdingTree) - Method in class moa.classifiers.trees.HoeffdingTree.InactiveLearningNode
learnFromInstance(Instance, HoeffdingTree) - Method in class moa.classifiers.trees.HoeffdingTree.LearningNode
learnFromInstance(Instance, HoeffdingTree) - Method in class moa.classifiers.trees.HoeffdingTree.LearningNodeNBAdaptive
learnFromInstance(Instance, HoeffdingTree) - Method in class moa.classifiers.trees.LimAttHoeffdingTree.LearningNodeNBAdaptive
learnFromInstance(Instance, HoeffdingTree) - Method in class moa.classifiers.trees.LimAttHoeffdingTree.LimAttLearningNode
learnFromInstance(Instance, HoeffdingTree) - Method in class moa.classifiers.trees.RandomHoeffdingTree.LearningNodeNBAdaptive
learnFromInstance(Instance, HoeffdingTree) - Method in class moa.classifiers.trees.RandomHoeffdingTree.RandomLearningNode
LearningCurve - Class in moa.evaluation: Class that stores and keeps the history of evaluation measurements.
LearningCurve(String) - Constructor for class moa.evaluation.LearningCurve
LearningEvaluation - Class in moa.evaluation: Class that stores an array of evaluation measurements.
LearningEvaluation(Measurement[]) - Constructor for class moa.evaluation.LearningEvaluation
LearningEvaluation(Measurement[], ClassificationPerformanceEvaluator, Classifier) - Constructor for class moa.evaluation.LearningEvaluation
LearningEvaluation(ClassificationPerformanceEvaluator, Classifier) - Constructor for class moa.evaluation.LearningEvaluation
LearningEvaluation(Measurement[], LearningPerformanceEvaluator, Clusterer) - Constructor for class moa.evaluation.LearningEvaluation
learningModel - Variable in class moa.classifiers.trees.FIMTDD.LeafNode
learningModel - Variable in class moa.classifiers.trees.ORTO.ActiveLearningNode
learningNode - Variable in class moa.classifiers.rules.core.Rule
LearningPerformanceEvaluator - Interface in moa.evaluation: Interface implemented by learner evaluators to monitor the results of the learning process.
learningRateDecay - Variable in class moa.classifiers.rules.functions.Perceptron
learningRateDecayFactorOption - Variable in class moa.classifiers.trees.FIMTDD
learningRateDecayOption - Variable in class moa.classifiers.rules.functions.Perceptron
learningRateOption - Variable in class moa.classifiers.functions.SGD
learningRateOption - Variable in class moa.classifiers.functions.SGDMultiClass
learningRatio - Variable in class moa.classifiers.rules.functions.Perceptron
learningRatioConstOption - Variable in class moa.classifiers.trees.FIMTDD
LearningRatioDecayOrConstOption - Variable in class moa.classifiers.trees.ORTO
learningRatioOption - Variable in class moa.classifiers.functions.Perceptron
learningRatioOption - Variable in class moa.classifiers.meta.LimAttClassifier
learningRatioOption - Variable in class moa.classifiers.rules.AMRulesRegressor
learningRatioOption - Variable in class moa.classifiers.rules.core.Rule.Builder
learningRatioOption - Variable in class moa.classifiers.rules.functions.Perceptron
learningRatioOption - Variable in class moa.classifiers.trees.FIMTDD
LearningRatioOption - Variable in class moa.classifiers.trees.ORTO
LearnModel - Class in moa.tasks: Task for learning a model without any evaluation.
LearnModel() - Constructor for class moa.tasks.LearnModel
LearnModel(Classifier, InstanceStream, int, int) - Constructor for class moa.tasks.LearnModel
LearnModelRegression - Class in moa.tasks: Task for learning a model without any evaluation.
LearnModelRegression() - Constructor for class moa.tasks.LearnModelRegression
LearnModelRegression(Classifier, InstanceStream, int, int) - Constructor for class moa.tasks.LearnModelRegression
learnObject(double[]) - Method in class moa.clusterers.outliers.AnyOut.AnyOutCore
learnRateDecay - Variable in class moa.classifiers.trees.ORTO
LEDGenerator - Class in moa.streams.generators: Stream generator for the problem of predicting the digit displayed on a 7-segment LED display.
LEDGenerator() - Constructor for class moa.streams.generators.LEDGenerator
LEDGeneratorDrift - Class in moa.streams.generators: Stream generator for the problem of predicting the digit displayed on a 7-segment LED display with drift.
LEDGeneratorDrift() - Constructor for class moa.streams.generators.LEDGeneratorDrift
left - Variable in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserver.Node
left - Variable in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserverRegression.Node
left - Variable in class moa.classifiers.core.attributeclassobservers.FIMTDDNumericAttributeClassObserver.Node
leftStatistics - Variable in class moa.classifiers.core.attributeclassobservers.FIMTDDNumericAttributeClassObserver.Node
legendLocationOption - Variable in class moa.tasks.Plot: Legend (key) location on the plot.
legendTypeOption - Variable in class moa.tasks.Plot: Legend elements' alignment.
length - Variable in class moa.clusterers.streamkm.StreamKM
length() - Method in class moa.evaluation.WindowClassificationPerformanceEvaluator.Estimator
lenWindow - Variable in class moa.evaluation.WindowClassificationPerformanceEvaluator.Estimator
lenWindow - Variable in class moa.evaluation.WindowRegressionPerformanceEvaluator.Estimator
lessThan - Variable in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserverRegression.Node
leveraginBagAlgorithmOption - Variable in class moa.classifiers.meta.LeveragingBag
LeveragingBag - Class in moa.classifiers.meta: Leveraging Bagging for evolving data streams using ADWIN.
LeveragingBag() - Constructor for class moa.classifiers.meta.LeveragingBag
LimAttClassifier - Class in moa.classifiers.meta: Ensemble Combining Restricted Hoeffding Trees using Stacking.
LimAttClassifier() - Constructor for class moa.classifiers.meta.LimAttClassifier
LimAttClassifier.CombinationGenerator - Class in moa.classifiers.meta
LimAttClassifier.CombinationGenerator(int, int) - Constructor for class moa.classifiers.meta.LimAttClassifier.CombinationGenerator
LimAttHoeffdingTree - Class in moa.classifiers.trees: Hoeffding decision trees with a restricted number of attributes for data streams.
LimAttHoeffdingTree() - Constructor for class moa.classifiers.trees.LimAttHoeffdingTree
LimAttHoeffdingTree.LearningNodeNB - Class in moa.classifiers.trees
LimAttHoeffdingTree.LearningNodeNB(double[]) - Constructor for class moa.classifiers.trees.LimAttHoeffdingTree.LearningNodeNB
LimAttHoeffdingTree.LearningNodeNBAdaptive - Class in moa.classifiers.trees
LimAttHoeffdingTree.LearningNodeNBAdaptive(double[]) - Constructor for class moa.classifiers.trees.LimAttHoeffdingTree.LearningNodeNBAdaptive
LimAttHoeffdingTree.LimAttLearningNode - Class in moa.classifiers.trees
LimAttHoeffdingTree.LimAttLearningNode(double[]) - Constructor for class moa.classifiers.trees.LimAttHoeffdingTree.LimAttLearningNode
limitOption - Variable in class moa.classifiers.lazy.kNN
LinearNNSearch - Class in moa.classifiers.lazy.neighboursearch: Class implementing the brute force search algorithm for nearest neighbour search.
LinearNNSearch() - Constructor for class moa.classifiers.lazy.neighboursearch.LinearNNSearch: Constructor.
LinearNNSearch(Instances) - Constructor for class moa.classifiers.lazy.neighboursearch.LinearNNSearch: Constructor that uses the supplied set of instances.
linearOption - Variable in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble: Determines whether additional information should be sent to the output.
LineGraphViewPanel - Class in moa.gui: This panel displays an evaluation learning curve.
LineGraphViewPanel() - Constructor for class moa.gui.LineGraphViewPanel
LineGraphViewPanel.PlotLine - Class in moa.gui
LineGraphViewPanel.PlotLine() - Constructor for class moa.gui.LineGraphViewPanel.PlotLine
LineGraphViewPanel.PlotPanel - Class in moa.gui
LineGraphViewPanel.PlotPanel() - Constructor for class moa.gui.LineGraphViewPanel.PlotPanel
LineGraphViewPanel.PlotTableModel - Class in moa.gui
LineGraphViewPanel.PlotTableModel() - Constructor for class moa.gui.LineGraphViewPanel.PlotTableModel
lineWidthOption - Variable in class moa.tasks.Plot: Plotted line width.
listAttributes - Variable in class moa.classifiers.meta.RandomRules
listAttributes - Variable in class moa.classifiers.trees.LimAttHoeffdingTree.LimAttLearningNode
listAttributes - Variable in class moa.classifiers.trees.LimAttHoeffdingTree
listAttributes - Variable in class moa.classifiers.trees.RandomHoeffdingTree.RandomLearningNode
ListOption - Class in moa.options: List option.
ListOption(String, char, String, Option, Option[], char) - Constructor for class moa.options.ListOption
listOptions() - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.MOA: Returns an enumeration describing the available options.
listOptions() - Method in class weka.datagenerators.classifiers.classification.MOA: Returns an enumeration describing the available options.
lloydPlusPlus(int, int, int, Point[], Point[]) - Method in class moa.clusterers.streamkm.StreamKM
logKm1 - Variable in class moa.classifiers.meta.OzaBoostAdwin
LOGLOSS - Static variable in class moa.classifiers.functions.SGD
LOGLOSS - Static variable in class moa.classifiers.functions.SGDMultiClass
LOGLOSS - Static variable in class moa.classifiers.functions.SPegasos
lossExamplesSeen - Variable in class moa.classifiers.trees.FIMTDD.SplitNode
lossFadedSumAlternate - Variable in class moa.classifiers.trees.FIMTDD.SplitNode
lossFadedSumOriginal - Variable in class moa.classifiers.trees.FIMTDD.SplitNode
lossFunctionOption - Variable in class moa.classifiers.functions.SGD
lossFunctionOption - Variable in class moa.classifiers.functions.SGDMultiClass
lossFunctionOption - Variable in class moa.classifiers.functions.SPegasos
lossNumQiTests - Variable in class moa.classifiers.trees.FIMTDD.SplitNode
lossStatistics - Variable in class moa.classifiers.trees.ORTO.InnerNode
lossSumQi - Variable in class moa.classifiers.trees.FIMTDD.SplitNode
lowerBound - Variable in class moa.classifiers.core.attributeclassobservers.VFMLNumericAttributeClassObserver.Bin
lRate - Variable in class moa.recommender.rc.predictor.impl.BRISMFPredictor
lRateOption - Variable in class moa.recommender.predictor.BRISMFPredictor
LS - Variable in class moa.cluster.CFCluster: Linear sum of all the points added to the cluster.
LST - Variable in class moa.clusterers.clustream.ClustreamKernel
lt_cnt - Variable in class moa.clusterers.outliers.AbstractC.ISBIndex.ISBNode

M

m_A - Variable in class moa.streams.generators.multilabel.MetaMultilabelGenerator
m_ActiveIndices - Variable in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: The boolean flags, whether an attribute will be used or not.
m_ActualClassifier - Variable in class weka.classifiers.meta.MOA: the actual moa classifier to use for learning.
m_ActualGenerator - Variable in class weka.datagenerators.classifiers.classification.MOA: the actual data generator.
m_acuity - Variable in class moa.clusterers.CobWeb: Acuity (minimum standard deviation).
m_bias - Variable in class moa.classifiers.functions.SGD
m_bias - Variable in class moa.classifiers.functions.SGDMultiClass
m_BinaryGenerator - Variable in class moa.streams.generators.multilabel.MetaMultilabelGenerator
m_Classifier - Variable in class weka.classifiers.meta.MOA: the moa classifier option (this object is used in the GenericObjectEditor).
m_classTotals - Variable in class moa.classifiers.bayes.NaiveBayesMultinomial: sum of weight_of_instance * word_count_of_instance for each class
m_cobwebTree - Variable in class moa.clusterers.CobWeb: Holds the root of the Cobweb tree.
m_CustomEditor - Variable in class weka.gui.MOAClassOptionEditor: the custom editor.
m_cutoff - Variable in class moa.clusterers.CobWeb: Cutoff (minimum category utility).
m_Data - Variable in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: the instances used internally.
m_Distance - Variable in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborNode: The distance from the current instance to this neighbor.
m_DistanceFunction - Variable in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch: the distance function used.
m_DistanceList - Variable in class moa.classifiers.lazy.neighboursearch.KDTree: Array holding the distances of the nearest neighbours.
m_Distances - Variable in class moa.classifiers.lazy.neighboursearch.LinearNNSearch: Array holding the distances of the nearest neighbours.
m_DontNormalize - Variable in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: True if normalization is turned off (default false).
m_EditComponent - Variable in class weka.gui.MOAClassOptionEditor: the component for editing.
m_End - Variable in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNode: The end index of the portion of the master index array, which stores indices of the instances/points the node contains.
m_EuclideanDistance - Variable in class moa.classifiers.lazy.neighboursearch.KDTree: The euclidean distance function to use.
m_EuclideanDistance - Variable in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter: The distance function used for building the tree.
m_First - Variable in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborList: The first node in the list.
m_Fraction - Variable in class moa.clusterers.outliers.AbstractC.AbstractCBase
m_Generator - Variable in class weka.datagenerators.classifiers.classification.MOA: for manipulating the generator through the GUI.
m_headerInfo - Variable in class moa.classifiers.bayes.NaiveBayesMultinomial: copy of header information for use in toString method
m_Instance - Variable in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborNode: The neighbor instance.
m_Instances - Variable in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter: The instances that'll be used for tree construction.
m_Instances - Variable in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch: The neighbourhood of instances to find neighbours in.
m_InstancesTemplate - Variable in class moa.core.utils.Converter
m_InstList - Variable in class moa.classifiers.lazy.neighboursearch.KDTree: Indexlist of the instances of this kdtree.
m_InstList - Variable in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter: The master index array that'll be reshuffled as nodes are split and the tree is constructed.
m_k - Variable in class moa.clusterers.outliers.Angiulli.STORMBase
m_k - Variable in class moa.clusterers.outliers.MCOD.MCODBase
m_k - Variable in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
m_kNN - Variable in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch: The number of neighbours to find.
m_L - Variable in class moa.classifiers.multilabel.MEKAClassifier
m_L - Variable in class moa.classifiers.multilabel.meta.MLOzaBag
m_L - Variable in class moa.classifiers.multilabel.meta.MLOzaBagAdwin
m_L - Variable in class moa.classifiers.multilabel.MultilabelHoeffdingTree
m_L - Variable in class moa.core.utils.Converter
m_L - Variable in class moa.streams.generators.multilabel.MetaMultilabelGenerator
m_lambda - Variable in class moa.classifiers.functions.SGD: The regularization parameter
m_lambda - Variable in class moa.classifiers.functions.SGDMultiClass: The regularization parameter
m_lambda - Variable in class moa.classifiers.functions.SPegasos: The regularization parameter
m_Last - Variable in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborList: The last node in the list.
m_learningRate - Variable in class moa.classifiers.functions.SGD: The learning rate
m_learningRate - Variable in class moa.classifiers.functions.SGDMultiClass: The learning rate
m_Left - Variable in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNode: left subtree; contains instances with smaller or equal to split value.
m_Length - Variable in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborList: The number of nodes to attempt to maintain in the list.
m_loss - Variable in class moa.classifiers.functions.SGD: The current loss function to minimize
m_loss - Variable in class moa.classifiers.functions.SGDMultiClass: The current loss function to minimize
m_loss - Variable in class moa.classifiers.functions.SPegasos: The current loss function to minimize
m_MaxDepth - Variable in class moa.classifiers.lazy.neighboursearch.KDTree: Tree stats.
m_MaxInstInLeaf - Variable in class moa.classifiers.lazy.neighboursearch.KDTree: maximal number of instances in a leaf.
m_MeasurePerformance - Variable in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch: Should we measure Performance.
m_MetaRandom - Variable in class moa.streams.generators.multilabel.MetaMultilabelGenerator
m_MinBoxRelWidth - Variable in class moa.classifiers.lazy.neighboursearch.KDTree: minimal relative width of a KDTree rectangle.
m_MultilabelInstancesHeader - Variable in class moa.streams.generators.multilabel.MetaMultilabelGenerator
m_nBothInlierOutlier - Variable in class moa.clusterers.outliers.AbstractC.AbstractCBase
m_nBothInlierOutlier - Variable in class moa.clusterers.outliers.Angiulli.STORMBase
m_nBothInlierOutlier - Variable in class moa.clusterers.outliers.MCOD.MCODBase
m_nBothInlierOutlier - Variable in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
m_Next - Variable in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborNode: A link to the next neighbor instance.
m_NodeNumber - Variable in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNode: node number (only for debug).
m_NodeRanges - Variable in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNode: lowest and highest value and width (= high - low) for each dimension.
m_NodesRectBounds - Variable in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNode: The lo and high bounds of the hyper rectangle described by the node.
m_nOnlyInlier - Variable in class moa.clusterers.outliers.AbstractC.AbstractCBase
m_nOnlyInlier - Variable in class moa.clusterers.outliers.Angiulli.STORMBase
m_nOnlyInlier - Variable in class moa.clusterers.outliers.MCOD.MCODBase
m_nOnlyInlier - Variable in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
m_nOnlyOutlier - Variable in class moa.clusterers.outliers.AbstractC.AbstractCBase
m_nOnlyOutlier - Variable in class moa.clusterers.outliers.Angiulli.STORMBase
m_nOnlyOutlier - Variable in class moa.clusterers.outliers.MCOD.MCODBase
m_nOnlyOutlier - Variable in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
m_normal - Static variable in class moa.clusterers.CobWeb: Normal constant.
m_NormalizeNodeWidth - Variable in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter: Stores whether if the width of a KDTree node is normalized or not.
m_numberMerges - Variable in class moa.clusterers.CobWeb: the number of merges that happened
m_numberOfClusters - Variable in class moa.clusterers.CobWeb: Number of clusters (nodes in the tree).
m_numberOfClustersDetermined - Variable in class moa.clusterers.CobWeb: whether the number of clusters was already determined
m_numberSplits - Variable in class moa.clusterers.CobWeb: the number of splits that happened
m_numClasses - Variable in class moa.classifiers.bayes.NaiveBayesMultinomial: number of class values
m_numInstances - Variable in class moa.classifiers.functions.SGD: The number of training instances
m_numInstances - Variable in class moa.classifiers.functions.SGDMultiClass: The number of training instances
m_NumLeaves - Variable in class moa.classifiers.lazy.neighboursearch.KDTree: Tree stats.
m_NumNodes - Variable in class moa.classifiers.lazy.neighboursearch.KDTree: Tree stats.
m_outlier - Variable in class moa.gui.visualization.RunOutlierVisualizer
m_Present - Static variable in class moa.core.SizeOf: whether the agent is present.
m_probOfClass - Variable in class moa.classifiers.bayes.NaiveBayesMultinomial: the probability of a class (i.e.
m_QueryFreq - Variable in class moa.clusterers.outliers.Angiulli.STORMBase
m_radius - Variable in class moa.clusterers.outliers.AbstractC.AbstractCBase
m_radius - Variable in class moa.clusterers.outliers.Angiulli.STORMBase
m_radius - Variable in class moa.clusterers.outliers.MCOD.MCODBase
m_radius - Variable in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
m_Ranges - Variable in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: The range of the attributes.
m_Right - Variable in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNode: right subtree; contains instances with larger than split value.
m_Root - Variable in class moa.classifiers.lazy.neighboursearch.KDTree: The root node of the tree.
m_saveInstances - Variable in class moa.clusterers.CobWeb: Output instances in graph representation of Cobweb tree (Allows instances at nodes in the tree to be visualized in the Explorer).
m_SkipIdentical - Variable in class moa.classifiers.lazy.neighboursearch.LinearNNSearch: Whether to skip instances from the neighbours that are identical to the query instance.
m_SplitDim - Variable in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNode: attribute to split on.
m_Splitter - Variable in class moa.classifiers.lazy.neighboursearch.KDTree: The node splitter.
m_SplitValue - Variable in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNode: value to split on.
m_Start - Variable in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNode: The start index of the portion of the master index array, which stores the indices of the instances/points the node contains.
m_t - Variable in class moa.classifiers.functions.SGD: Holds the current iteration number
m_t - Variable in class moa.classifiers.functions.SGDMultiClass: Holds the current iteration number
m_t - Variable in class moa.classifiers.functions.SPegasos: Holds the current iteration number
m_theta - Variable in class moa.clusterers.outliers.MCOD.MCODBase
m_TopCombinations - Variable in class moa.streams.generators.multilabel.MetaMultilabelGenerator
m_Validated - Variable in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Whether all the necessary preparations have been done.
m_weights - Variable in class moa.classifiers.functions.SGD: Stores the weights (+ bias in the last element)
m_weights - Variable in class moa.classifiers.functions.SGDMultiClass: Stores the weights (+ bias in the last element)
m_weights - Variable in class moa.classifiers.functions.SPegasos: Stores the weights (+ bias in the last element)
m_WindowSize - Variable in class moa.clusterers.outliers.AbstractC.AbstractCBase
m_WindowSize - Variable in class moa.clusterers.outliers.Angiulli.STORMBase
m_WindowSize - Variable in class moa.clusterers.outliers.MCOD.MCODBase
m_WindowSize - Variable in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
m_wordTotalForClass - Variable in class moa.classifiers.bayes.NaiveBayesMultinomial: probability that a word (w) exists in a class (H) (i.e.
magChangeOption - Variable in class moa.streams.generators.HyperplaneGenerator
main(String[]) - Static method in class moa.clusterers.outliers.AbstractC.Test
main(String[]) - Static method in class moa.clusterers.outliers.Angiulli.Test
main(String[]) - Static method in class moa.clusterers.outliers.MCOD.Test
main(String[]) - Static method in class moa.clusterers.outliers.SimpleCOD.Test
main(String[]) - Static method in class moa.clusterers.outliers.TestSpeed
main(String[]) - Static method in class moa.DoTask: Main method for running tasks from the command line.
main(String[]) - Static method in class moa.gui.BatchCmd
main(String[]) - Static method in class moa.gui.conceptdrift.CDTaskManagerPanel
main(String[]) - Static method in class moa.gui.GUI
main(String[]) - Static method in class moa.gui.GUIDefaults: only for testing - prints the content of the props file.
main(String[]) - Static method in class moa.gui.OptionsConfigurationPanel
main(String[]) - Static method in class moa.gui.RegressionTaskManagerPanel
main(String[]) - Static method in class moa.gui.TaskLauncher
main(String[]) - Static method in class moa.gui.TaskManagerPanel
main(String[]) - Static method in class moa.MakeObject: Main method for writing an object to a file from the command line.
main(String[]) - Static method in class moa.streams.generators.multilabel.MetaMultilabelGenerator
main(String[]) - Static method in class weka.classifiers.meta.MOA: Main method for testing this class.
main(String[]) - Static method in class weka.datagenerators.classifiers.classification.MOA: Main method for executing this class.
mainFindBestValEntropy(BinaryTreeNumericAttributeClassObserver.Node) - Method in class moa.classifiers.rules.RuleClassifier
MainTask - Class in moa.tasks: Abstract Main Task.
MainTask() - Constructor for class moa.tasks.MainTask
MajorityClass - Class in moa.classifiers.functions: Majority class learner.
MajorityClass() - Constructor for class moa.classifiers.functions.MajorityClass
MajorityLabelset - Class in moa.classifiers.multilabel: Majority Labelset classifier.
MajorityLabelset() - Constructor for class moa.classifiers.multilabel.MajorityLabelset
MakeObject - Class in moa: Class for writing a MOA object to a file from the command line.
MakeObject() - Constructor for class moa.MakeObject
makeOlder(long, double) - Method in class moa.clusterers.clustree.ClusKernel: Make this cluster older.
makeOlder(long, double) - Method in class moa.clusterers.clustree.Entry: Ages this entrie's data AND buffer according to the given time and aging constant.
makeOlder(long, double) - Method in class moa.clusterers.clustree.Node
manageMemory(int, int) - Method in class moa.classifiers.bayes.NaiveBayes
manageMemory(int, int) - Method in class moa.classifiers.rules.RuleClassifier
manager - Variable in class moa.clusterers.streamkm.StreamKM
manipulateIds() - Method in class moa.clusterers.outliers.AnyOut.util.DataSet: resets the ids, so that the set contains ids from 0 to noOfObjects-1
marker - Variable in class moa.classifiers.lazy.kNNwithPAW
marker - Variable in class moa.classifiers.lazy.kNNwithPAWandADWIN
materializeObject(TaskMonitor, ObjectRepository) - Method in class moa.options.AbstractClassOption: Gets a materialized object of this option.
matrixCodes - Variable in class moa.classifiers.meta.LeveragingBag
matrixCodes - Variable in class moa.classifiers.meta.LimAttClassifier
matrixCodes - Variable in class moa.classifiers.meta.OzaBoostAdwin
maturityOption - Variable in class moa.classifiers.meta.DACC: Maturity age of classifiers
MAX - Static variable in class moa.classifiers.lazy.neighboursearch.KDTree: The index of MAX value in attributes' range array.
MAX - Static variable in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter: Index of max value in an array of attributes' range.
MAX_PANEL_HEIGHT - Static variable in class moa.gui.OptionsConfigurationPanel
MAX_STATUS_STRING_LENGTH - Static variable in class moa.DoTask: Maximum length of the status string that shows the progress of tasks running.
maxBranches() - Method in class moa.classifiers.core.conditionaltests.InstanceConditionalBinaryTest
maxBranches() - Method in class moa.classifiers.core.conditionaltests.InstanceConditionalTest: Gets the number of maximum branches, -1 if unknown.
maxBranches() - Method in class moa.classifiers.core.conditionaltests.NominalAttributeMultiwayTest
MAXBUCKETS - Static variable in class moa.classifiers.core.driftdetection.ADWIN
maxBucketsize - Variable in class moa.clusterers.streamkm.BucketManager
maxByteSizeOption - Variable in class moa.classifiers.meta.AccuracyUpdatedEnsemble: Determines the maximum size of model (evaluated after every chunk).
maxByteSizeOption - Variable in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble: Determines the maximum size of model (evaluated after every chunk).
maxByteSizeOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree
maxByteSizeOption - Variable in class moa.classifiers.trees.HoeffdingTree
maxDepth - Variable in class moa.classifiers.trees.ORTO
maxHeight - Variable in class moa.clusterers.clustree.ClusTree: The maximal height of the tree.
maxHeightOption - Variable in class moa.clusterers.clustree.ClusTree
maxID - Variable in class moa.classifiers.trees.FIMTDD
maxID - Variable in class moa.classifiers.trees.ORTO
maximumCacheSizeOption - Variable in class moa.tasks.CacheShuffledStream
maxIndex() - Method in class moa.core.DoubleVector
maxInstancesOption - Variable in class moa.tasks.EvaluateModel
maxInstancesOption - Variable in class moa.tasks.EvaluateModelRegression
maxInstancesOption - Variable in class moa.tasks.LearnModel
maxInstancesOption - Variable in class moa.tasks.LearnModelRegression
maxInstancesOption - Variable in class moa.tasks.WriteStreamToARFFFile
maxInstInLeafTipText() - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Tip text for this property.
maxMemberCount - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble
maxMemoryOption - Variable in class moa.tasks.EvaluateInterleavedChunks: Allows to define the memory limit for the created model.
maxNodeCapacity - Variable in class moa.clusterers.outliers.utils.mtree.MTree
maxNodes - Variable in class moa.classifiers.rules.core.attributeclassobservers.FIMTDDNumericAttributeClassLimitObserver
maxNodesOption - Variable in class moa.classifiers.rules.core.attributeclassobservers.FIMTDDNumericAttributeClassLimitObserver
maxNumKernelsOption - Variable in class moa.clusterers.clustream.Clustream
maxNumKernelsOption - Variable in class moa.clusterers.clustream.WithKmeans
MaxOptionLevelOption - Variable in class moa.classifiers.trees.ORTO
maxOptionPathsOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree
MAXPERMANENT - Static variable in class moa.classifiers.meta.ADACC: Maximum number of snapshots (copies of classifiers kept in case of recurrence)
maxPosterior - Variable in class moa.classifiers.active.ActiveClassifier
maxPredictionPaths - Variable in class moa.classifiers.trees.HoeffdingOptionTree
maxRating - Variable in class moa.recommender.rc.data.impl.MemRecommenderData
maxSize - Variable in class moa.classifiers.trees.ASHoeffdingTree
maxStoredCount - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble
maxTreeDepthOption - Variable in class moa.streams.generators.RandomTreeGenerator
MaxTreesOption - Variable in class moa.classifiers.trees.ORTO
maxVal - Variable in class moa.options.FloatOption
maxVal - Variable in class moa.options.IntOption
maxValueObservedPerClass - Variable in class moa.classifiers.core.attributeclassobservers.GaussianNumericAttributeClassObserver
mc - Variable in class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
mcc - Variable in class moa.clusterers.outliers.MCOD.MicroCluster
mcCorrectWeight - Variable in class moa.classifiers.trees.AdaHoeffdingOptionTree.AdaLearningNode
mcCorrectWeight - Variable in class moa.classifiers.trees.HoeffdingOptionTree.LearningNodeNBAdaptive
mcCorrectWeight - Variable in class moa.classifiers.trees.HoeffdingTree.LearningNodeNBAdaptive
mcCorrectWeight - Variable in class moa.classifiers.trees.LimAttHoeffdingTree.LearningNodeNBAdaptive
mcCorrectWeight - Variable in class moa.classifiers.trees.RandomHoeffdingTree.LearningNodeNBAdaptive
MCOD - Class in moa.clusterers.outliers.MCOD
MCOD() - Constructor for class moa.clusterers.outliers.MCOD.MCOD
MCODBase - Class in moa.clusterers.outliers.MCOD
MCODBase() - Constructor for class moa.clusterers.outliers.MCOD.MCODBase
MCODBase.EventItem - Class in moa.clusterers.outliers.MCOD
MCODBase.EventItem(ISBIndex.ISBNode, Long) - Constructor for class moa.clusterers.outliers.MCOD.MCODBase.EventItem
MCODBase.EventQueue - Class in moa.clusterers.outliers.MCOD
MCODBase.EventQueue() - Constructor for class moa.clusterers.outliers.MCOD.MCODBase.EventQueue
mean - Variable in class moa.core.GaussianEstimator
measureByteSize() - Method in class moa.AbstractMOAObject
measureByteSize(MOAObject) - Static method in class moa.AbstractMOAObject: Gets the memory size of an object.
measureByteSize() - Method in class moa.classifiers.trees.HoeffdingOptionTree
measureByteSize() - Method in class moa.classifiers.trees.HoeffdingTree
measureByteSize() - Method in class moa.core.AutoExpandVector
measureByteSize() - Method in interface moa.MOAObject: Gets the memory size of this object.
MeasureCollection - Class in moa.evaluation
MeasureCollection() - Constructor for class moa.evaluation.MeasureCollection
measureCollectionTypeOption - Variable in class moa.tasks.EvaluateClustering
measureMaxDepth() - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Returns the depth of the tree.
Measurement - Class in moa.core: Class for storing an evaluation measurement.
Measurement(String, double) - Constructor for class moa.core.Measurement
measurementNames - Variable in class moa.evaluation.LearningCurve
measurements - Variable in class moa.evaluation.LearningEvaluation
measurementValues - Variable in class moa.evaluation.LearningCurve
measureNumLeaves() - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Returns the number of leaves.
measureObjectByteSize(Serializable) - Static method in class moa.core.SerializeUtils
measurePerformanceTipText() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch: Returns the tip text for this property.
MeasureStreamSpeed - Class in moa.tasks: Task for measuring the speed of the stream.
MeasureStreamSpeed() - Constructor for class moa.tasks.MeasureStreamSpeed
measureTreeDepth() - Method in class moa.classifiers.trees.HoeffdingOptionTree
measureTreeDepth() - Method in class moa.classifiers.trees.HoeffdingTree
measureTreeSize() - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Returns the size of the tree.
MedianOfWidestDimension - Class in moa.classifiers.lazy.neighboursearch.kdtrees: The class that splits a KDTree node based on the median value of a dimension in which the node's points have the widest spread.

For more information see also:

Jerome H.
MedianOfWidestDimension() - Constructor for class moa.classifiers.lazy.neighboursearch.kdtrees.MedianOfWidestDimension
MEKAClassifier - Class in moa.classifiers.multilabel: Class for using a MEKA classifier.
MEKAClassifier() - Constructor for class moa.classifiers.multilabel.MEKAClassifier
memberCountOption - Variable in class moa.classifiers.meta.AccuracyUpdatedEnsemble: Number of component classifiers.
memberCountOption - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble: Number of component classifiers.
memberCountOption - Variable in class moa.classifiers.meta.DACC: Ensemble size
memberCountOption - Variable in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble: Number of component classifiers.
MembershipMatrix - Class in moa.evaluation
MembershipMatrix(Clustering, ArrayList<DataPoint>) - Constructor for class moa.evaluation.MembershipMatrix
memCheckFrequencyOption - Variable in class moa.tasks.EvaluateInterleavedChunks: Allows to define the frequency of memory checks.
memCheckFrequencyOption - Variable in class moa.tasks.EvaluateInterleavedTestThenTrain
memCheckFrequencyOption - Variable in class moa.tasks.EvaluatePrequential
memCheckFrequencyOption - Variable in class moa.tasks.EvaluatePrequentialRegression
memCheckFrequencyOption - Variable in class moa.tasks.LearnModel
memCheckFrequencyOption - Variable in class moa.tasks.LearnModelRegression
memoryEstimatePeriodOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree
memoryEstimatePeriodOption - Variable in class moa.classifiers.trees.HoeffdingTree
memoryStrategyOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree
MemRecommenderData - Class in moa.recommender.data
MemRecommenderData() - Constructor for class moa.recommender.data.MemRecommenderData
MemRecommenderData - Class in moa.recommender.rc.data.impl
MemRecommenderData() - Constructor for class moa.recommender.rc.data.impl.MemRecommenderData
MemRecommenderData.RatingIterator - Class in moa.recommender.rc.data.impl
merge(SphereCluster) - Method in class moa.cluster.SphereCluster
mergeEntries(int, int) - Method in class moa.clusterers.clustree.Node: Merge the two entries at the given position.
mergeWith(Entry) - Method in class moa.clusterers.clustree.Entry: Merge this entry witht the given Entry.
merit - Variable in class moa.classifiers.core.AttributeSplitSuggestion
MetaMultilabelGenerator - Class in moa.streams.generators.multilabel: Stream generator for multilabel data.
MetaMultilabelGenerator() - Constructor for class moa.streams.generators.multilabel.MetaMultilabelGenerator
metaRandomSeedOption - Variable in class moa.streams.generators.multilabel.MetaMultilabelGenerator
MicroCluster - Class in moa.clusterers.denstream
MicroCluster(double[], int, long, double, Timestamp) - Constructor for class moa.clusterers.denstream.MicroCluster
MicroCluster(Instance, int, long, double, Timestamp) - Constructor for class moa.clusterers.denstream.MicroCluster
MicroCluster - Class in moa.clusterers.outliers.MCOD
MicroCluster(ISBIndex.ISBNode) - Constructor for class moa.clusterers.outliers.MCOD.MicroCluster
MidPointOfWidestDimension - Class in moa.classifiers.lazy.neighboursearch.kdtrees: The class that splits a KDTree node based on the midpoint value of a dimension in which the node's points have the widest spread.

For more information see also:

Andrew Moore (1991).
MidPointOfWidestDimension() - Constructor for class moa.classifiers.lazy.neighboursearch.kdtrees.MidPointOfWidestDimension
MILLISECS_BETWEEN_REFRESH - Static variable in class moa.gui.conceptdrift.CDTaskManagerPanel
MILLISECS_BETWEEN_REFRESH - Static variable in class moa.gui.RegressionTaskManagerPanel
MILLISECS_BETWEEN_REFRESH - Static variable in class moa.gui.TaskManagerPanel
MIN - Static variable in class moa.classifiers.lazy.neighboursearch.KDTree: The index of MIN value in attributes' range array.
MIN - Static variable in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter: Index of min value in an array of attributes' range.
MIN_VARIANCE - Static variable in class moa.clusterers.clustream.ClustreamKernel
MIN_VARIANCE - Static variable in class moa.clusterers.clustree.ClusKernel
minBoxRelWidthTipText() - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Tip text for this property.
minBranchFracOption - Variable in class moa.classifiers.core.splitcriteria.InfoGainSplitCriterion
Miniball - Class in moa.cluster: Java Porting of the Miniball.h code of Bernd Gaertner.
Miniball(int) - Constructor for class moa.cluster.Miniball
minimumValue - Variable in class moa.classifiers.rules.driftdetection.PageHinkleyTest
minMax(Iterable<T>) - Static method in class moa.clusterers.outliers.utils.mtree.utils.Utils: Identifies the minimum and maximum elements from an iterable, according to the natural ordering of the elements.
minNodeCapacity - Variable in class moa.clusterers.outliers.utils.mtree.MTree
minNumInstancesOption - Variable in class moa.classifiers.core.driftdetection.CusumDM
minNumInstancesOption - Variable in class moa.classifiers.core.driftdetection.DDM
minNumInstancesOption - Variable in class moa.classifiers.core.driftdetection.EnsembleDriftDetectionMethods
minNumInstancesOption - Variable in class moa.classifiers.core.driftdetection.EWMAChartDM
minNumInstancesOption - Variable in class moa.classifiers.core.driftdetection.GeometricMovingAverageDM
minNumInstancesOption - Variable in class moa.classifiers.core.driftdetection.PageHinkleyDM
minRating - Variable in class moa.recommender.rc.data.impl.MemRecommenderData
minVal - Variable in class moa.options.FloatOption
minVal - Variable in class moa.options.IntOption
minValueObservedPerClass - Variable in class moa.classifiers.core.attributeclassobservers.GaussianNumericAttributeClassObserver
minWeight() - Method in class moa.core.DoubleVector
MiscUtils - Class in moa.core: Class implementing some utility methods.
MiscUtils() - Constructor for class moa.core.MiscUtils
missingWeightObserved - Variable in class moa.classifiers.core.attributeclassobservers.NominalAttributeClassObserver
MLOzaBag - Class in moa.classifiers.multilabel.meta: OzaBag for Multi-label data.
MLOzaBag() - Constructor for class moa.classifiers.multilabel.meta.MLOzaBag
MLOzaBagAdwin - Class in moa.classifiers.multilabel.meta: MLOzaBagAdwin: Changes the way to compute accuracy as an input for Adwin
MLOzaBagAdwin() - Constructor for class moa.classifiers.multilabel.meta.MLOzaBagAdwin
moa - package moa
MOA - Class in weka.classifiers.meta: Wrapper for MOA classifiers.

Since MOA doesn't offer a mechanism to query a classifier for the types of attributes and classes it can handle, the capabilities of this wrapper are hard-coded: nominal and numeric attributes and only nominal class attributes are allowed.
MOA() - Constructor for class weka.classifiers.meta.MOA
MOA - Class in weka.datagenerators.classifiers.classification: A wrapper around MOA instance streams.
MOA() - Constructor for class weka.datagenerators.classifiers.classification.MOA
moa.classifiers - package moa.classifiers
moa.classifiers.active - package moa.classifiers.active
moa.classifiers.bayes - package moa.classifiers.bayes
moa.classifiers.core - package moa.classifiers.core
moa.classifiers.core.attributeclassobservers - package moa.classifiers.core.attributeclassobservers
moa.classifiers.core.conditionaltests - package moa.classifiers.core.conditionaltests
moa.classifiers.core.driftdetection - package moa.classifiers.core.driftdetection
moa.classifiers.core.splitcriteria - package moa.classifiers.core.splitcriteria
moa.classifiers.drift - package moa.classifiers.drift
moa.classifiers.functions - package moa.classifiers.functions
moa.classifiers.lazy - package moa.classifiers.lazy
moa.classifiers.lazy.neighboursearch - package moa.classifiers.lazy.neighboursearch
moa.classifiers.lazy.neighboursearch.kdtrees - package moa.classifiers.lazy.neighboursearch.kdtrees
moa.classifiers.meta - package moa.classifiers.meta
moa.classifiers.multilabel - package moa.classifiers.multilabel
moa.classifiers.multilabel.meta - package moa.classifiers.multilabel.meta
moa.classifiers.rules - package moa.classifiers.rules
moa.classifiers.rules.core - package moa.classifiers.rules.core
moa.classifiers.rules.core.attributeclassobservers - package moa.classifiers.rules.core.attributeclassobservers
moa.classifiers.rules.core.conditionaltests - package moa.classifiers.rules.core.conditionaltests
moa.classifiers.rules.core.splitcriteria - package moa.classifiers.rules.core.splitcriteria
moa.classifiers.rules.core.voting - package moa.classifiers.rules.core.voting
moa.classifiers.rules.driftdetection - package moa.classifiers.rules.driftdetection
moa.classifiers.rules.functions - package moa.classifiers.rules.functions
moa.classifiers.rules.nodes - package moa.classifiers.rules.nodes
moa.classifiers.trees - package moa.classifiers.trees
moa.cluster - package moa.cluster
moa.clusterers - package moa.clusterers
moa.clusterers.clustream - package moa.clusterers.clustream
moa.clusterers.clustree - package moa.clusterers.clustree
moa.clusterers.clustree.util - package moa.clusterers.clustree.util
moa.clusterers.denstream - package moa.clusterers.denstream
moa.clusterers.macro - package moa.clusterers.macro
moa.clusterers.macro.dbscan - package moa.clusterers.macro.dbscan
moa.clusterers.outliers - package moa.clusterers.outliers
moa.clusterers.outliers.AbstractC - package moa.clusterers.outliers.AbstractC
moa.clusterers.outliers.Angiulli - package moa.clusterers.outliers.Angiulli
moa.clusterers.outliers.AnyOut - package moa.clusterers.outliers.AnyOut
moa.clusterers.outliers.AnyOut.util - package moa.clusterers.outliers.AnyOut.util
moa.clusterers.outliers.MCOD - package moa.clusterers.outliers.MCOD
moa.clusterers.outliers.SimpleCOD - package moa.clusterers.outliers.SimpleCOD
moa.clusterers.outliers.utils.mtree - package moa.clusterers.outliers.utils.mtree
moa.clusterers.outliers.utils.mtree.utils - package moa.clusterers.outliers.utils.mtree.utils
moa.clusterers.streamkm - package moa.clusterers.streamkm
moa.core - package moa.core
moa.core.utils - package moa.core.utils
moa.evaluation - package moa.evaluation
moa.gui - package moa.gui
moa.gui.clustertab - package moa.gui.clustertab
moa.gui.conceptdrift - package moa.gui.conceptdrift
moa.gui.outliertab - package moa.gui.outliertab
moa.gui.visualization - package moa.gui.visualization
moa.learners - package moa.learners
moa.options - package moa.options
moa.recommender.data - package moa.recommender.data
moa.recommender.dataset - package moa.recommender.dataset
moa.recommender.dataset.impl - package moa.recommender.dataset.impl
moa.recommender.predictor - package moa.recommender.predictor
moa.recommender.rc.data - package moa.recommender.rc.data
moa.recommender.rc.data.impl - package moa.recommender.rc.data.impl
moa.recommender.rc.predictor - package moa.recommender.rc.predictor
moa.recommender.rc.predictor.impl - package moa.recommender.rc.predictor.impl
moa.recommender.rc.utils - package moa.recommender.rc.utils
moa.streams - package moa.streams
moa.streams.clustering - package moa.streams.clustering
moa.streams.filters - package moa.streams.filters
moa.streams.generators - package moa.streams.generators
moa.streams.generators.cd - package moa.streams.generators.cd
moa.streams.generators.multilabel - package moa.streams.generators.multilabel
moa.tasks - package moa.tasks
MOAClassOptionEditor - Class in weka.gui: An editor for MOA ClassOption objects.
MOAClassOptionEditor() - Constructor for class weka.gui.MOAClassOptionEditor
MOAObject - Interface in moa: Interface implemented by classes in MOA, so that all are serializable, can produce copies of their objects, and can measure its memory size.
MOAUtils - Class in weka.core: A helper class for MOA related classes.
MOAUtils() - Constructor for class weka.core.MOAUtils
modelAttIndexToInstanceAttIndex(int, Instance) - Static method in class moa.classifiers.AbstractClassifier: Gets the index of the attribute in the instance, given the index of the attribute in the learner.
modelAttIndexToInstanceAttIndex(int, Instances) - Static method in class moa.classifiers.AbstractClassifier: Gets the index of the attribute in a set of instances, given the index of the attribute in the learner.
modelAttIndexToInstanceAttIndex(int, Instance) - Static method in class moa.classifiers.rules.AbstractAMRules: Gets the index of the attribute in the instance, given the index of the attribute in the learner.
modelAttIndexToInstanceAttIndex(int, Instance) - Static method in class moa.clusterers.AbstractClusterer
modelAttIndexToInstanceAttIndex(int, Instances) - Static method in class moa.clusterers.AbstractClusterer
modelContext - Variable in class moa.classifiers.AbstractClassifier: Header of the instances of the data stream
modelContext - Variable in class moa.clusterers.AbstractClusterer
modelOption - Variable in class moa.tasks.EvaluateModel
modelOption - Variable in class moa.tasks.EvaluateModelRegression
modelRandomSeedOption - Variable in class moa.streams.clustering.RandomRBFGeneratorEvents
modelRandomSeedOption - Variable in class moa.streams.generators.RandomRBFGenerator
modifyDependencyMatrix(boolean[][], double, Random) - Method in class moa.streams.generators.multilabel.MetaMultilabelGenerator: ModifyDependencyMatrix.
modifyPriorVector(double[], double, Random, boolean) - Method in class moa.streams.generators.multilabel.MetaMultilabelGenerator: ModifyPriorVector.
monitorMeanDecr(double, double) - Method in class moa.classifiers.core.driftdetection.HDDM_W_Test
monitorMeanIncr(double, double) - Method in class moa.classifiers.core.driftdetection.HDDM_W_Test
moreImprovementsPossible(int, double) - Method in class moa.clusterers.outliers.AnyOut.AnyOutCore
mouseClicked(int, int) - Method in interface moa.gui.AWTInteractiveRenderer
MovielensDataset - Class in moa.recommender.dataset.impl
MovielensDataset() - Constructor for class moa.recommender.dataset.impl.MovielensDataset
mse_r - Variable in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble: The mean square residual in a given moment, based on a window of latest examples.
MTRandom - Class in moa.clusterers.streamkm
MTRandom() - Constructor for class moa.clusterers.streamkm.MTRandom: The default constructor for an instance of MTRandom.
MTRandom(boolean) - Constructor for class moa.clusterers.streamkm.MTRandom: This version of the constructor can be used to implement identical behaviour to the original C code version of this algorithm including exactly replicating the case where the seed value had not been set prior to calling genrand_int32.
MTRandom(long) - Constructor for class moa.clusterers.streamkm.MTRandom: This version of the constructor simply initialises the class with the given 64 bit seed value.
MTRandom(byte[]) - Constructor for class moa.clusterers.streamkm.MTRandom: This version of the constructor initialises the class with the given byte array.
MTRandom(int[]) - Constructor for class moa.clusterers.streamkm.MTRandom: This version of the constructor initialises the class with the given integer array.
MTree<DATA> - Class in moa.clusterers.outliers.utils.mtree: The main class that implements the M-Tree.
MTree(DistanceFunction<? super DATA>, SplitFunction<DATA>) - Constructor for class moa.clusterers.outliers.utils.mtree.MTree: Constructs an M-Tree with the specified distance function.
MTree(int, DistanceFunction<? super DATA>, SplitFunction<DATA>) - Constructor for class moa.clusterers.outliers.utils.mtree.MTree: Constructs an M-Tree with the specified minimum node capacity and distance function.
MTree(int, int, DistanceFunction<? super DATA>, SplitFunction<DATA>) - Constructor for class moa.clusterers.outliers.utils.mtree.MTree: Constructs an M-Tree with the specified minimum and maximum node capacities and distance function.
MTree.Query - Class in moa.clusterers.outliers.utils.mtree: An Iterable class which can be iterated to fetch the results of a nearest-neighbors query.
MTree.ResultItem - Class in moa.clusterers.outliers.utils.mtree: The type of the results for nearest-neighbor queries.
mtreeMC - Variable in class moa.clusterers.outliers.MCOD.MCODBase
MultiChoiceOption - Class in moa.options: Multi choice option.
MultiChoiceOption(String, char, String, String[], String[], int) - Constructor for class moa.options.MultiChoiceOption
MultiChoiceOptionEditComponent - Class in moa.gui: An OptionEditComponent that lets the user edit a multi choice option.
MultiChoiceOptionEditComponent(MultiChoiceOption) - Constructor for class moa.gui.MultiChoiceOptionEditComponent
MultiFilteredStream - Class in moa.streams: Class for representing a stream that is filtered.
MultiFilteredStream() - Constructor for class moa.streams.MultiFilteredStream
MultilabelArffFileStream - Class in moa.streams.generators.multilabel: Stream reader for ARFF files of multilabel data.
MultilabelArffFileStream() - Constructor for class moa.streams.generators.multilabel.MultilabelArffFileStream
MultilabelArffFileStream(String, int) - Constructor for class moa.streams.generators.multilabel.MultilabelArffFileStream
MultilabelHoeffdingTree - Class in moa.classifiers.multilabel: Hoeffding Tree for classifying multi-label data.
MultilabelHoeffdingTree() - Constructor for class moa.classifiers.multilabel.MultilabelHoeffdingTree
MultilabelHoeffdingTree.MultilabelInactiveLearningNode - Class in moa.classifiers.multilabel
MultilabelHoeffdingTree.MultilabelInactiveLearningNode(double[]) - Constructor for class moa.classifiers.multilabel.MultilabelHoeffdingTree.MultilabelInactiveLearningNode
MultilabelHoeffdingTree.MultilabelLearningNodeClassifier - Class in moa.classifiers.multilabel
MultilabelHoeffdingTree.MultilabelLearningNodeClassifier(double[], Classifier, MultilabelHoeffdingTree) - Constructor for class moa.classifiers.multilabel.MultilabelHoeffdingTree.MultilabelLearningNodeClassifier
MultilabelInstance - Class in moa.core: Multilabel instance.
MultilabelInstance() - Constructor for class moa.core.MultilabelInstance
MultilabelInstancesHeader - Class in moa.core: Class for storing the header or context of a multilabel data stream.
MultilabelInstancesHeader(Instances, int) - Constructor for class moa.core.MultilabelInstancesHeader
multilabelStreamTemplate - Variable in class moa.streams.generators.multilabel.MetaMultilabelGenerator
MultilabelWindowClassificationPerformanceEvaluator - Class in moa.evaluation: Multilabel Window Classification Performance Evaluator.
MultilabelWindowClassificationPerformanceEvaluator() - Constructor for class moa.evaluation.MultilabelWindowClassificationPerformanceEvaluator
multivariateAnomalyProbabilityThresholdOption - Variable in class moa.classifiers.rules.AbstractAMRules
muOption - Variable in class moa.clusterers.denstream.WithDBSCAN
mVisibleColors - Static variable in class moa.clusterers.macro.ColorArray
MyBaseOutlierDetector - Class in moa.clusterers.outliers
MyBaseOutlierDetector() - Constructor for class moa.clusterers.outliers.MyBaseOutlierDetector
MyBaseOutlierDetector.Outlier - Class in moa.clusterers.outliers
MyBaseOutlierDetector.Outlier(Instance, long, Object) - Constructor for class moa.clusterers.outliers.MyBaseOutlierDetector.Outlier
MyBaseOutlierDetector.OutlierNotifier - Class in moa.clusterers.outliers
MyBaseOutlierDetector.OutlierNotifier() - Constructor for class moa.clusterers.outliers.MyBaseOutlierDetector.OutlierNotifier
MyBaseOutlierDetector.PrintMsg - Interface in moa.clusterers.outliers
MyBaseOutlierDetector.ProgressInfo - Interface in moa.clusterers.outliers
MyBaseOutlierDetector.StdPrintMsg - Class in moa.clusterers.outliers
MyBaseOutlierDetector.StdPrintMsg() - Constructor for class moa.clusterers.outliers.MyBaseOutlierDetector.StdPrintMsg
MyBaseOutlierDetector.StdPrintMsg(String) - Constructor for class moa.clusterers.outliers.MyBaseOutlierDetector.StdPrintMsg
myOut - Variable in class moa.clusterers.outliers.MyBaseOutlierDetector
myProgressInfo - Variable in class moa.clusterers.outliers.MyBaseOutlierDetector

N

n - Variable in class moa.classifiers.rules.functions.TargetMean
N - Variable in class moa.cluster.CFCluster: Number of points in the cluster.
n_max - Variable in class moa.classifiers.core.driftdetection.HDDM_A_Test
n_min - Variable in class moa.classifiers.core.driftdetection.HDDM_A_Test
NaiveBayes - Class in moa.classifiers.bayes: Naive Bayes incremental learner.
NaiveBayes() - Constructor for class moa.classifiers.bayes.NaiveBayes
NaiveBayesMultinomial - Class in moa.classifiers.bayes: Class for building and using a multinomial Naive Bayes classifier.
NaiveBayesMultinomial() - Constructor for class moa.classifiers.bayes.NaiveBayesMultinomial
name - Variable in class moa.core.Measurement
name - Variable in class moa.options.AbstractOption: Name of this option.
nameIsLegal(String) - Static method in class moa.options.AbstractOption: Gets whether the name is valid or not.
nanoTimeToSeconds(long) - Static method in class moa.core.TimingUtils
nbCorrectWeight - Variable in class moa.classifiers.trees.AdaHoeffdingOptionTree.AdaLearningNode
nbCorrectWeight - Variable in class moa.classifiers.trees.HoeffdingOptionTree.LearningNodeNBAdaptive
nbCorrectWeight - Variable in class moa.classifiers.trees.HoeffdingTree.LearningNodeNBAdaptive
nbCorrectWeight - Variable in class moa.classifiers.trees.LimAttHoeffdingTree.LearningNodeNBAdaptive
nbCorrectWeight - Variable in class moa.classifiers.trees.RandomHoeffdingTree.LearningNodeNBAdaptive
nbInstances - Variable in class moa.classifiers.meta.DACC: Number of instances from the stream
nbThresholdOption - Variable in class moa.classifiers.rules.RuleClassifierNBayes
nbThresholdOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree
nbThresholdOption - Variable in class moa.classifiers.trees.HoeffdingTree
nearestEntry(ClusKernel) - Method in class moa.clusterers.clustree.Node: Returns the neareast Entry to the given Cluster.
nearestEntry(Entry) - Method in class moa.clusterers.clustree.Node: Return the nearest entry to the given one.
nearestNeighbour(Instance) - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Returns the nearest neighbour of the supplied target instance.
nearestNeighbour(Instance) - Method in class moa.classifiers.lazy.neighboursearch.LinearNNSearch: Returns the nearest instance in the current neighbourhood to the supplied instance.
nearestNeighbour(Instance) - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch: Returns the nearest instance in the current neighbourhood to the supplied instance.
NearestNeighbourSearch - Class in moa.classifiers.lazy.neighboursearch: Abstract class for nearest neighbour search.
NearestNeighbourSearch() - Constructor for class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch: Constructor.
NearestNeighbourSearch(Instances) - Constructor for class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch: Constructor.
NearestNeighbourSearch.MyHeap - Class in moa.classifiers.lazy.neighboursearch: A class for a heap to store the nearest k neighbours to an instance.
NearestNeighbourSearch.MyHeap(int) - Constructor for class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.MyHeap: constructor.
NearestNeighbourSearch.MyHeapElement - Class in moa.classifiers.lazy.neighboursearch: A class for storing data about a neighboring instance.
NearestNeighbourSearch.MyHeapElement(int, double) - Constructor for class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.MyHeapElement: constructor.
NearestNeighbourSearch.NeighborList - Class in moa.classifiers.lazy.neighboursearch: A class for a linked list to store the nearest k neighbours to an instance.
NearestNeighbourSearch.NeighborList(int) - Constructor for class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborList: Creates the neighborlist with a desired length.
NearestNeighbourSearch.NeighborNode - Class in moa.classifiers.lazy.neighboursearch: A class for storing data about a neighboring instance.
NearestNeighbourSearch.NeighborNode(double, Instance, NearestNeighbourSearch.NeighborNode) - Constructor for class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborNode: Create a new neighbor node.
NearestNeighbourSearch.NeighborNode(double, Instance) - Constructor for class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborNode: Create a new neighbor node that doesn't link to any other nodes.
nearestNeighbourSearchOption - Variable in class moa.classifiers.lazy.kNN
negLambda - Variable in class moa.clusterers.clustree.ClusTree: Parameter for the weighting function use to weight the entries.
nError - Variable in class moa.classifiers.rules.functions.TargetMean
nEstimacion - Variable in class moa.classifiers.core.driftdetection.HDDM_A_Test
newclassifier - Variable in class moa.classifiers.drift.DriftDetectionMethodClassifier
newClassifierReset - Variable in class moa.classifiers.drift.DriftDetectionMethodClassifier
newErrorWeightedVote() - Method in class moa.classifiers.rules.AbstractAMRules
newErrorWeightedVote() - Method in class moa.classifiers.rules.AMRulesRegressor
newLeafModel() - Method in class moa.classifiers.trees.FIMTDD
newLeafNode() - Method in class moa.classifiers.trees.FIMTDD
newLearningNode(double[]) - Method in class moa.classifiers.multilabel.HoeffdingTreeClassifLeaves
newLearningNode(double[], Classifier) - Method in class moa.classifiers.multilabel.HoeffdingTreeClassifLeaves
newLearningNode(double[]) - Method in class moa.classifiers.multilabel.MultilabelHoeffdingTree
newLearningNode(double[], Classifier) - Method in class moa.classifiers.multilabel.MultilabelHoeffdingTree
newLearningNode(double[]) - Method in class moa.classifiers.trees.AdaHoeffdingOptionTree
newLearningNode(double[]) - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree
newLearningNode() - Method in class moa.classifiers.trees.HoeffdingOptionTree
newLearningNode(double[]) - Method in class moa.classifiers.trees.HoeffdingOptionTree
newLearningNode() - Method in class moa.classifiers.trees.HoeffdingTree
newLearningNode(double[]) - Method in class moa.classifiers.trees.HoeffdingTree
newLearningNode(double[]) - Method in class moa.classifiers.trees.LimAttHoeffdingTree
newLearningNode(double[]) - Method in class moa.classifiers.trees.RandomHoeffdingTree
newline - Static variable in class moa.core.StringUtils
newNominalClassObserver() - Method in class moa.classifiers.bayes.NaiveBayes
newNominalClassObserver() - Method in class moa.classifiers.rules.RuleClassifier
newNominalClassObserver() - Method in class moa.classifiers.trees.DecisionStump
newNominalClassObserver() - Method in class moa.classifiers.trees.HoeffdingOptionTree
newNominalClassObserver() - Method in class moa.classifiers.trees.HoeffdingTree
newNumericClassObserver() - Method in class moa.classifiers.bayes.NaiveBayes
newNumericClassObserver() - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
newNumericClassObserver() - Method in class moa.classifiers.rules.RuleClassifier
newNumericClassObserver() - Method in class moa.classifiers.trees.DecisionStump
newNumericClassObserver() - Method in class moa.classifiers.trees.FIMTDD
newNumericClassObserver() - Method in class moa.classifiers.trees.HoeffdingOptionTree
newNumericClassObserver() - Method in class moa.classifiers.trees.HoeffdingTree
newNumericClassObserver() - Method in class moa.classifiers.trees.ORTO
newNumericClassObserver2() - Method in class moa.classifiers.rules.RuleClassifier
newRule(int, RuleActiveLearningNode, double[]) - Method in class moa.classifiers.rules.AbstractAMRules: Rule.Builder() to build an object with the parameters.
newRule(int, RuleActiveLearningNode, double[]) - Method in class moa.classifiers.rules.AMRulesRegressor
newRuleActiveLearningNode(Rule.Builder) - Method in class moa.classifiers.rules.AbstractAMRules
newRuleActiveLearningNode(double[]) - Method in class moa.classifiers.rules.AbstractAMRules
newRuleActiveLearningNode(Rule.Builder) - Method in class moa.classifiers.rules.AMRulesRegressor
newRuleActiveLearningNode(double[]) - Method in class moa.classifiers.rules.AMRulesRegressor
newSplitNode(InstanceConditionalTest) - Method in class moa.classifiers.trees.FIMTDD
newSplitNode(InstanceConditionalTest, double[]) - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree
newSplitNode(InstanceConditionalTest, double[], int) - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree
newSplitNode(InstanceConditionalTest, double[], int) - Method in class moa.classifiers.trees.HoeffdingTree
newSplitNode(InstanceConditionalTest, double[]) - Method in class moa.classifiers.trees.HoeffdingTree
newThreshold - Variable in class moa.classifiers.active.ActiveClassifier
next(int) - Method in class moa.clusterers.streamkm.MTRandom: This method forms the basis for generating a pseudo random number sequence from this class.
next() - Method in interface moa.recommender.dataset.Dataset
next() - Method in class moa.recommender.dataset.impl.FlixsterDataset
next() - Method in class moa.recommender.dataset.impl.JesterDataset
next() - Method in class moa.recommender.dataset.impl.MovielensDataset
next() - Method in class moa.recommender.rc.data.impl.MemRecommenderData.RatingIterator
next() - Method in class moa.recommender.rc.utils.DenseVector.DenseVectorIterator
next() - Method in class moa.recommender.rc.utils.SparseVector.SparseVectorIterator
nextClassShouldBeZero - Variable in class moa.streams.generators.AgrawalGenerator
nextClassShouldBeZero - Variable in class moa.streams.generators.SEAGenerator
nextClassShouldBeZero - Variable in class moa.streams.generators.STAGGERGenerator
nextInstance() - Method in class moa.streams.ArffFileStream
nextInstance() - Method in class moa.streams.CachedInstancesStream
nextInstance() - Method in class moa.streams.clustering.FileStream
nextInstance() - Method in class moa.streams.clustering.RandomRBFGeneratorEvents
nextInstance() - Method in class moa.streams.ConceptDriftRealStream
nextInstance() - Method in class moa.streams.ConceptDriftStream
nextInstance() - Method in class moa.streams.FilteredStream
nextInstance() - Method in class moa.streams.filters.AddNoiseFilter
nextInstance() - Method in class moa.streams.filters.CacheFilter
nextInstance() - Method in class moa.streams.filters.ReplacingMissingValuesFilter
nextInstance() - Method in class moa.streams.generators.AgrawalGenerator
nextInstance() - Method in class moa.streams.generators.cd.AbstractConceptDriftGenerator
nextInstance() - Method in class moa.streams.generators.HyperplaneGenerator
nextInstance() - Method in class moa.streams.generators.LEDGenerator
nextInstance() - Method in class moa.streams.generators.LEDGeneratorDrift
nextInstance() - Method in class moa.streams.generators.multilabel.MetaMultilabelGenerator: GenerateML.
nextInstance() - Method in class moa.streams.generators.RandomRBFGenerator
nextInstance() - Method in class moa.streams.generators.RandomRBFGeneratorDrift
nextInstance() - Method in class moa.streams.generators.RandomTreeGenerator
nextInstance() - Method in class moa.streams.generators.SEAGenerator
nextInstance() - Method in class moa.streams.generators.STAGGERGenerator
nextInstance() - Method in class moa.streams.generators.WaveformGenerator
nextInstance() - Method in class moa.streams.generators.WaveformGeneratorDrift
nextInstance() - Method in interface moa.streams.InstanceStream: Gets the next instance from this stream.
nextInstance() - Method in class moa.streams.MultiFilteredStream
nextOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
nextValue() - Method in class moa.streams.generators.cd.AbruptChangeGenerator
nextValue() - Method in class moa.streams.generators.cd.AbstractConceptDriftGenerator
nextValue() - Method in class moa.streams.generators.cd.GradualChangeGenerator
nextValue() - Method in class moa.streams.generators.cd.NoChangeGenerator
nFeatures - Variable in class moa.recommender.rc.predictor.impl.BRISMFPredictor
nInlier - Variable in class moa.clusterers.outliers.AbstractC.ISBIndex.ISBNode
nInlier - Variable in class moa.clusterers.outliers.Angiulli.ISBIndex.ISBNode
nInlier - Variable in class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
nInlier - Variable in class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBNode
nItems - Variable in class moa.recommender.rc.data.impl.MemRecommenderData
nIterations - Variable in class moa.recommender.rc.predictor.impl.BRISMFPredictor
noAnomalyDetectionOption - Variable in class moa.classifiers.rules.AbstractAMRules
NoChange - Class in moa.classifiers.functions: NoChange class classifier.
NoChange() - Constructor for class moa.classifiers.functions.NoChange
NoChangeGenerator - Class in moa.streams.generators.cd
NoChangeGenerator() - Constructor for class moa.streams.generators.cd.NoChangeGenerator
node - Variable in class moa.classifiers.trees.HoeffdingOptionTree.FoundNode
node - Variable in class moa.classifiers.trees.HoeffdingTree.FoundNode
Node - Class in moa.clusterers.clustree
Node(int, int) - Constructor for class moa.clusterers.clustree.Node: Initialze a normal node, which is not fake.
Node(int, int, int, boolean) - Constructor for class moa.clusterers.clustree.Node: Initialiazes a node which is a fake root depending on the given boolean.
Node(int, int, Entry[]) - Constructor for class moa.clusterers.clustree.Node: USED FOR EM_TOP_DOWN BULK LOADING
node - Variable in class moa.clusterers.outliers.AbstractC.ISBIndex.ISBSearchResult
node - Variable in class moa.clusterers.outliers.Angiulli.ISBIndex.ISBSearchResult
node - Variable in class moa.clusterers.outliers.MCOD.ISBIndex.ISBSearchResult
node - Variable in class moa.clusterers.outliers.MCOD.MCODBase.EventItem
node - Variable in class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBSearchResult
node - Variable in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase.EventItem
nodeList - Variable in class moa.classifiers.rules.core.Rule
nodes - Variable in class moa.clusterers.outliers.MCOD.MicroCluster
nodeSplitterTipText() - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Returns the tip text for this property.
nodesReinsert - Variable in class moa.clusterers.outliers.MCOD.MCODBase
nodeStatistics - Variable in class moa.classifiers.rules.core.RuleActiveLearningNode
nodeStatistics - Variable in class moa.classifiers.trees.ORTO.ActiveLearningNode
nodesToAdapt - Variable in class moa.classifiers.trees.ORTO
nodeType - Variable in class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
noiseInClusterOption - Variable in class moa.streams.clustering.RandomRBFGeneratorEvents
noiseLabel - Variable in class moa.gui.visualization.DataPoint
noiseLevelOption - Variable in class moa.streams.clustering.RandomRBFGeneratorEvents
noisePercentageOption - Variable in class moa.streams.generators.HyperplaneGenerator
noisePercentageOption - Variable in class moa.streams.generators.LEDGenerator
noisePercentageOption - Variable in class moa.streams.generators.SEAGenerator
NominalAttributeBinaryRulePredicate - Class in moa.classifiers.rules.core.conditionaltests: Nominal binary conditional test for instances to use to split nodes in rules.
NominalAttributeBinaryRulePredicate(int, int) - Constructor for class moa.classifiers.rules.core.conditionaltests.NominalAttributeBinaryRulePredicate
NominalAttributeBinaryTest - Class in moa.classifiers.core.conditionaltests: Nominal binary conditional test for instances to use to split nodes in Hoeffding trees.
NominalAttributeBinaryTest(int, int) - Constructor for class moa.classifiers.core.conditionaltests.NominalAttributeBinaryTest
NominalAttributeClassObserver - Class in moa.classifiers.core.attributeclassobservers: Class for observing the class data distribution for a nominal attribute.
NominalAttributeClassObserver() - Constructor for class moa.classifiers.core.attributeclassobservers.NominalAttributeClassObserver
NominalAttributeMultiwayTest - Class in moa.classifiers.core.conditionaltests: Nominal multi way conditional test for instances to use to split nodes in Hoeffding trees.
NominalAttributeMultiwayTest(int) - Constructor for class moa.classifiers.core.conditionaltests.NominalAttributeMultiwayTest
nominalEstimatorOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree
nominalEstimatorOption - Variable in class moa.classifiers.trees.HoeffdingTree
nominalReplacementStrategyOption - Variable in class moa.streams.filters.ReplacingMissingValuesFilter
nominalSelectedStrategy - Variable in class moa.streams.filters.ReplacingMissingValuesFilter
NonConvexCluster - Class in moa.clusterers.macro
NonConvexCluster(CFCluster, List<CFCluster>) - Constructor for class moa.clusterers.macro.NonConvexCluster
noOfKthNearest() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.MyHeap: returns the number of k nearest.
noPrePruneOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree
noPrePruneOption - Variable in class moa.classifiers.trees.HoeffdingTree
norm(double, int) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Normalizes a given value of a numeric attribute.
norm() - Method in class moa.recommender.rc.utils.Vector
NORMAL_CONSTANT - Static variable in class moa.classifiers.rules.AbstractAMRules
NORMAL_CONSTANT - Static variable in class moa.core.GaussianEstimator
NormalizableDistance - Class in moa.classifiers.lazy.neighboursearch: Represents the abstract ancestor for normalizable distance functions, like Euclidean or Manhattan distance.
NormalizableDistance() - Constructor for class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Invalidates the distance function, Instances must be still set.
NormalizableDistance(Instances) - Constructor for class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Initializes the distance function and automatically initializes the ranges.
normalize(double[]) - Method in class moa.classifiers.rules.RuleClassifierNBayes
normalize() - Method in class moa.core.DoubleVector
normalizedInstance(Instance) - Method in class moa.classifiers.rules.functions.Perceptron
normalizedInstance(Instance, FIMTDD) - Method in class moa.classifiers.trees.FIMTDD.FIMTDDPerceptron
normalizedPrediction(Instance) - Method in class moa.classifiers.rules.functions.Perceptron
normalizeNodeWidthTipText() - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Tip text for this property.
normalizeOption - Variable in class moa.streams.clustering.FileStream
normalizeTargetValue(double) - Method in class moa.classifiers.trees.FIMTDD
normalizeWeights() - Method in class moa.classifiers.rules.functions.Perceptron
notBinaryStreamOption - Variable in class moa.streams.generators.cd.AbstractConceptDriftGenerator
notifyChangeListeners() - Method in class moa.gui.ClassOptionEditComponent: Notifies all registered change listeners that the options have changed.
notifyChangeListeners() - Method in class moa.gui.ClassOptionWithNamesEditComponent: Notifies all registered change listeners that the options have changed.
nOutlier - Variable in class moa.clusterers.outliers.AbstractC.ISBIndex.ISBNode
nOutlier - Variable in class moa.clusterers.outliers.Angiulli.ISBIndex.ISBNode
nOutlier - Variable in class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
nOutlier - Variable in class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBNode
nr_points() - Method in class moa.cluster.Miniball: Return the actual number of points in the list
nr_support_points() - Method in class moa.cluster.Miniball: Return the number of support points (used to calculate the miniball).
It's and internal info
nRangeQueriesExecuted - Variable in class moa.clusterers.outliers.MyBaseOutlierDetector
nRatings - Variable in class moa.recommender.rc.data.impl.MemRecommenderData
nTimePerObj - Variable in class moa.clusterers.outliers.MyBaseOutlierDetector
nTotalRunTime - Variable in class moa.clusterers.outliers.MyBaseOutlierDetector
NullAttributeClassObserver - Class in moa.classifiers.core.attributeclassobservers: Class for observing the class data distribution for a null attribute.
NullAttributeClassObserver() - Constructor for class moa.classifiers.core.attributeclassobservers.NullAttributeClassObserver
NullMonitor - Class in moa.tasks: Class that represents a null monitor.
NullMonitor() - Constructor for class moa.tasks.NullMonitor
nullString - Variable in class moa.options.AbstractClassOption: The null text.
NUM_BASE_ATTRIBUTES - Static variable in class moa.streams.generators.WaveformGenerator
NUM_CLASSES - Static variable in class moa.streams.generators.WaveformGenerator
NUM_IRRELEVANT_ATTRIBUTES - Static variable in class moa.streams.generators.LEDGenerator
numAttributes - Variable in class moa.classifiers.meta.RandomRules
numAttributes - Variable in class moa.classifiers.trees.LimAttHoeffdingTree.LimAttLearningNode
numAttributes - Variable in class moa.classifiers.trees.RandomHoeffdingTree.RandomLearningNode
numAttributes - Variable in class moa.streams.filters.ReplacingMissingValuesFilter
numAttributesOption - Variable in class moa.classifiers.meta.LimAttClassifier
numAttributesPercentageOption - Variable in class moa.classifiers.meta.RandomRules
numAttsOption - Variable in class moa.streams.clustering.ClusteringStream
numAttsOption - Variable in class moa.streams.generators.HyperplaneGenerator
numAttsOption - Variable in class moa.streams.generators.RandomRBFGenerator
numberAttribute - Variable in class moa.streams.generators.LEDGeneratorDrift
numberAttribute - Variable in class moa.streams.generators.WaveformGeneratorDrift
numberAttributes - Variable in class moa.classifiers.functions.Perceptron
numberAttributes - Variable in class moa.classifiers.meta.LimAttClassifier
numberAttributesDriftOption - Variable in class moa.streams.generators.LEDGeneratorDrift
numberAttributesDriftOption - Variable in class moa.streams.generators.WaveformGeneratorDrift
numberChanges - Variable in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
numberClasses - Variable in class moa.classifiers.functions.Perceptron
numberDetections - Variable in class moa.classifiers.functions.Perceptron
numberDetections - Variable in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
numberDetectionsOccurred - Variable in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
numberInstance - Variable in class moa.streams.generators.HyperplaneGenerator
numberInstances - Variable in class moa.classifiers.meta.WEKAClassifier
numberInstances - Variable in class moa.clusterers.streamkm.StreamKM
numberInstanceStream - Variable in class moa.streams.ConceptDriftRealStream
numberInstanceStream - Variable in class moa.streams.ConceptDriftStream
numberLeaves() - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaLearningNode
numberLeaves() - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaSplitNode
numberLeaves() - Method in interface moa.classifiers.trees.HoeffdingAdaptiveTree.NewNode
numberOfBuckets - Variable in class moa.clusterers.streamkm.BucketManager
numberOfCentres - Variable in class moa.clusterers.streamkm.StreamKM
numberOfChangesDetected - Variable in class moa.classifiers.meta.LeveragingBag
numberOfChangesDetected - Variable in class moa.classifiers.meta.LimAttClassifier
numberOfChangesDetected - Variable in class moa.classifiers.meta.OzaBoostAdwin
numberOfClusters() - Method in class moa.clusterers.CobWeb: Returns the number of clusters.
numberOfSamples - Variable in class moa.streams.filters.ReplacingMissingValuesFilter
numberWarnings - Variable in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
numBinsOption - Variable in class moa.classifiers.core.attributeclassobservers.GaussianNumericAttributeClassObserver
numBinsOption - Variable in class moa.classifiers.core.attributeclassobservers.VFMLNumericAttributeClassObserver
numBytesWritten - Variable in class moa.core.SerializeUtils.ByteCountingOutputStream
numCentroidsOption - Variable in class moa.streams.generators.RandomRBFGenerator
numChildren() - Method in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
numChildren() - Method in class moa.classifiers.trees.HoeffdingTree.SplitNode
numChildren() - Method in class moa.classifiers.trees.ORTO.InnerNode
numClasses - Variable in class moa.evaluation.BasicClassificationPerformanceEvaluator
numClasses - Variable in class moa.evaluation.WindowClassificationPerformanceEvaluator
numClasses - Variable in class moa.evaluation.WindowRegressionPerformanceEvaluator
numClassesOption - Variable in class moa.streams.generators.HyperplaneGenerator
numClassesOption - Variable in class moa.streams.generators.RandomRBFGenerator
numClassesOption - Variable in class moa.streams.generators.RandomTreeGenerator
numClusterOption - Variable in class moa.streams.clustering.RandomRBFGeneratorEvents
numClusterRangeOption - Variable in class moa.streams.clustering.RandomRBFGeneratorEvents
numClustersOption - Variable in class moa.clusterers.streamkm.StreamKM
numDriftAttsOption - Variable in class moa.streams.generators.HyperplaneGenerator
numDriftCentroidsOption - Variable in class moa.streams.generators.RandomRBFGeneratorDrift
numEnsemblePruningOption - Variable in class moa.classifiers.meta.LimAttClassifier
numEntries() - Method in class moa.evaluation.LearningCurve
numericalConstantValueOption - Variable in class moa.streams.filters.ReplacingMissingValuesFilter
numericalSelectedStrategy - Variable in class moa.streams.filters.ReplacingMissingValuesFilter
NumericAttributeBinaryRulePredicate - Class in moa.classifiers.rules.core.conditionaltests: Numeric binary conditional test for instances to use to split nodes in AMRules.
NumericAttributeBinaryRulePredicate(int, double, int) - Constructor for class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
NumericAttributeBinaryTest - Class in moa.classifiers.core.conditionaltests: Numeric binary conditional test for instances to use to split nodes in Hoeffding trees.
NumericAttributeBinaryTest(int, double, boolean) - Constructor for class moa.classifiers.core.conditionaltests.NumericAttributeBinaryTest
NumericAttributeClassObserver - Interface in moa.classifiers.core.attributeclassobservers: Interface for observing the class data distribution for a numeric attribute.
numericEstimatorOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree
numericEstimatorOption - Variable in class moa.classifiers.trees.HoeffdingTree
numericEstimatorOption - Variable in class moa.classifiers.trees.ORTO
numericObserverOption - Variable in class moa.classifiers.rules.AbstractAMRules
numericReplacementStrategyOption - Variable in class moa.streams.filters.ReplacingMissingValuesFilter
numFolds - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble
numFoldsOption - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble: Number of folds in candidate classifier cross-validation.
numFreeEntries() - Method in class moa.clusterers.clustree.Node: Return the number of free Entrys in this node.
numInitPoints - Variable in class moa.clusterers.denstream.WithDBSCAN
numInstances() - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNode: Returns the number of Instances in the rectangular region defined by this node.
numInstances - Variable in class moa.classifiers.meta.LimAttClassifier
numInstances - Variable in class moa.streams.generators.cd.AbstractConceptDriftGenerator
numInstancesConcept - Variable in class moa.streams.generators.SEAGenerator
numInstancesConceptOption - Variable in class moa.streams.generators.cd.AbstractConceptDriftGenerator
numInstancesInitOption - Variable in class moa.classifiers.active.ActiveClassifier
numInstancesRead - Variable in class moa.streams.ArffFileStream
numInstancesRead - Variable in class moa.streams.clustering.FileStream
numLabelsOption - Variable in class moa.streams.generators.multilabel.MetaMultilabelGenerator
numLabelsOption - Variable in class moa.streams.generators.multilabel.MultilabelArffFileStream
numNodes - Variable in class moa.classifiers.rules.core.attributeclassobservers.FIMTDDNumericAttributeClassLimitObserver
numNominalsOption - Variable in class moa.streams.generators.RandomTreeGenerator
numNonZeroEntries() - Method in class moa.core.DoubleVector
numNumericsOption - Variable in class moa.streams.generators.RandomTreeGenerator
numObservations - Variable in class moa.core.GreenwaldKhannaQuantileSummary
numOldLabelsOption - Variable in class moa.classifiers.meta.TemporallyAugmentedClassifier
numOptions() - Method in class moa.options.Options
numPassesOption - Variable in class moa.tasks.LearnModel
numPassesOption - Variable in class moa.tasks.LearnModelRegression
numProcessedPerUnit - Variable in class moa.clusterers.denstream.WithDBSCAN
numSplits() - Method in class moa.classifiers.core.AttributeSplitSuggestion
numSubsetsGreaterThanFrac(double[][], double) - Static method in class moa.classifiers.core.splitcriteria.InfoGainSplitCriterion
numTuples - Variable in class moa.core.GreenwaldKhannaQuantileSummary
numTuplesOption - Variable in class moa.classifiers.core.attributeclassobservers.GreenwaldKhannaNumericAttributeClassObserver
numValsPerNominalOption - Variable in class moa.streams.generators.RandomTreeGenerator
numValues() - Method in class moa.core.DoubleVector
nUsers - Variable in class moa.recommender.rc.data.impl.MemRecommenderData

O

oberversDistribProb(Instance, DoubleVector) - Method in class moa.classifiers.rules.RuleClassifier
obj - Variable in class moa.clusterers.outliers.AbstractC.ISBIndex.ISBNode
obj - Variable in class moa.clusterers.outliers.Angiulli.ISBIndex.ISBNode
obj - Variable in class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
obj - Variable in class moa.clusterers.outliers.MyBaseOutlierDetector.Outlier
obj - Variable in class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBNode
ObjectRepository - Interface in moa.core: Interface for object repositories.
objectToCLIString(Object, Class<?>) - Static method in class moa.options.ClassOption
objectToCLIString(Object, Class<?>) - Static method in class moa.options.ClassOptionWithNames
objectToCLIString(Object, Class<?>) - Static method in class moa.options.WEKAClassOption
objId - Variable in class moa.clusterers.outliers.AbstractC.AbstractCBase
objId - Variable in class moa.clusterers.outliers.Angiulli.STORMBase
objId - Variable in class moa.clusterers.outliers.MCOD.MCODBase
objId - Variable in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
obserClassDistrib - Variable in class moa.classifiers.rules.RuleClassification
observeAttributeClass(double, int, double) - Method in interface moa.classifiers.core.attributeclassobservers.AttributeClassObserver: Updates statistics of this observer given an attribute value, a class and the weight of the instance observed
observeAttributeClass(double, int, double) - Method in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserver
observeAttributeClass(double, int, double) - Method in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserverRegression
observeAttributeClass(double, double, double) - Method in class moa.classifiers.core.attributeclassobservers.FIMTDDNumericAttributeClassObserver
observeAttributeClass(double, int, double) - Method in class moa.classifiers.core.attributeclassobservers.GaussianNumericAttributeClassObserver
observeAttributeClass(double, int, double) - Method in class moa.classifiers.core.attributeclassobservers.GreenwaldKhannaNumericAttributeClassObserver
observeAttributeClass(double, int, double) - Method in class moa.classifiers.core.attributeclassobservers.NominalAttributeClassObserver
observeAttributeClass(double, int, double) - Method in class moa.classifiers.core.attributeclassobservers.NullAttributeClassObserver
observeAttributeClass(double, int, double) - Method in class moa.classifiers.core.attributeclassobservers.VFMLNumericAttributeClassObserver
observeAttributeClass(double, double, double) - Method in class moa.classifiers.rules.core.attributeclassobservers.FIMTDDNumericAttributeClassLimitObserver
observeAttributeTarget(double, double) - Method in interface moa.classifiers.core.attributeclassobservers.AttributeClassObserver
observeAttributeTarget(double, double) - Method in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserver
observeAttributeTarget(double, double) - Method in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserverRegression
observeAttributeTarget(double, double) - Method in class moa.classifiers.core.attributeclassobservers.GaussianNumericAttributeClassObserver
observeAttributeTarget(double, double) - Method in class moa.classifiers.core.attributeclassobservers.GreenwaldKhannaNumericAttributeClassObserver
observeAttributeTarget(double, double) - Method in class moa.classifiers.core.attributeclassobservers.NominalAttributeClassObserver
observeAttributeTarget(double, double) - Method in class moa.classifiers.core.attributeclassobservers.NullAttributeClassObserver
observeAttributeTarget(double, double) - Method in class moa.classifiers.core.attributeclassobservers.VFMLNumericAttributeClassObserver
observedClassDistribution - Variable in class moa.classifiers.bayes.NaiveBayes
observedClassDistribution - Variable in class moa.classifiers.functions.MajorityClass
observedClassDistribution - Variable in class moa.classifiers.rules.RuleClassifier
observedClassDistribution - Variable in class moa.classifiers.trees.DecisionStump
observedClassDistribution - Variable in class moa.classifiers.trees.HoeffdingOptionTree.Node
observedClassDistribution - Variable in class moa.classifiers.trees.HoeffdingTree.Node
observedClassDistributionIsPure() - Method in class moa.classifiers.trees.HoeffdingOptionTree.Node
observedClassDistributionIsPure() - Method in class moa.classifiers.trees.HoeffdingTree.Node
observers - Variable in class moa.classifiers.rules.RuleClassification
observersGauss - Variable in class moa.classifiers.rules.RuleClassification
OCBoost - Class in moa.classifiers.meta: Online Coordinate boosting for two classes evolving data streams.
OCBoost() - Constructor for class moa.classifiers.meta.OCBoost
oddsOffsetOption - Variable in class moa.classifiers.meta.LimAttClassifier
offlineOption - Variable in class moa.clusterers.denstream.WithDBSCAN
oldLabels - Variable in class moa.classifiers.meta.TemporallyAugmentedClassifier
oneSidedTest - Variable in class moa.classifiers.core.driftdetection.HDDM_W_Test
oneSidedTestOption - Variable in class moa.classifiers.core.driftdetection.HDDM_A_Test
oneSidedTestOption - Variable in class moa.classifiers.core.driftdetection.HDDM_W_Test
OnInlier(MyBaseOutlierDetector.Outlier) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector.OutlierNotifier
OnlineAccuracyUpdatedEnsemble - Class in moa.classifiers.meta: The online version of the Accuracy Updated Ensemble as proposed by Brzezinski and Stefanowski in "Combining block-based and online methods in learning ensembles from concept drifting data streams", Information Sciences, 2014.
OnlineAccuracyUpdatedEnsemble() - Constructor for class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble
OnlineAccuracyUpdatedEnsemble.ClassifierWithMemory - Class in moa.classifiers.meta
OnlineAccuracyUpdatedEnsemble.ClassifierWithMemory(Classifier, int) - Constructor for class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble.ClassifierWithMemory
OnlineSmoothBoost - Class in moa.classifiers.meta: Incremental on-line boosting with Theoretical Justifications of Shang-Tse Chen, Hsuan-Tien Lin and Chi-Jen Lu.
OnlineSmoothBoost() - Constructor for class moa.classifiers.meta.OnlineSmoothBoost
OnOutlier(MyBaseOutlierDetector.Outlier) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector.OutlierNotifier
operator - Variable in class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
operatorObserver - Variable in class moa.classifiers.rules.nodes.RuleSplitNode
Option - Interface in moa.options: Interface representing an option or parameter.
optionArrayToCLIString(Option[], char) - Static method in class moa.options.ListOption
optionCount - Variable in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
OptionDecayFactorOption - Variable in class moa.classifiers.trees.ORTO
optionDescriptions - Variable in class moa.options.MultiChoiceOption
OptionEditComponent - Interface in moa.gui: Interface representing a component to edit an option.
OptionFadingFactorOption - Variable in class moa.classifiers.trees.ORTO
optionFFSeen - Variable in class moa.classifiers.trees.ORTO.OptionNode
optionFFSSL - Variable in class moa.classifiers.trees.ORTO.OptionNode
OptionHandler - Interface in moa.options: Interface representing an object that handles options or parameters.
optionLabels - Variable in class moa.options.MultiChoiceOption
optionList - Variable in class moa.options.Options
OptionNodeAggregationOption - Variable in class moa.classifiers.trees.ORTO
options - Variable in class moa.gui.OptionsConfigurationPanel
options - Variable in class moa.options.AbstractOptionHandler: Options to handle
Options - Class in moa.options: File option.
Options() - Constructor for class moa.options.Options
OptionsConfigurationPanel - Class in moa.gui: This panel displays an options configuration.
OptionsConfigurationPanel(String, Options) - Constructor for class moa.gui.OptionsConfigurationPanel
orderedRulesOption - Variable in class moa.classifiers.rules.RuleClassifier
originalInstances - Static variable in class moa.streams.generators.LEDGenerator
originalNode - Variable in class moa.classifiers.trees.FIMTDD.Node
ORTO - Class in moa.classifiers.trees
ORTO() - Constructor for class moa.classifiers.trees.ORTO
ORTO.ActiveLearningNode - Class in moa.classifiers.trees
ORTO.ActiveLearningNode(int) - Constructor for class moa.classifiers.trees.ORTO.ActiveLearningNode
ORTO.InnerNode - Class in moa.classifiers.trees
ORTO.InnerNode(int) - Constructor for class moa.classifiers.trees.ORTO.InnerNode
ORTO.Node - Class in moa.classifiers.trees
ORTO.Node(int) - Constructor for class moa.classifiers.trees.ORTO.Node
ORTO.OptionNode - Class in moa.classifiers.trees
ORTO.OptionNode(int) - Constructor for class moa.classifiers.trees.ORTO.OptionNode
ORTO.ORTOPerceptron - Class in moa.classifiers.trees: A Perceptron classifier modified to conform to the specifications of Ikonomovska et al.
ORTO.ORTOPerceptron(ORTO.ORTOPerceptron) - Constructor for class moa.classifiers.trees.ORTO.ORTOPerceptron
ORTO.ORTOPerceptron() - Constructor for class moa.classifiers.trees.ORTO.ORTOPerceptron
ORTO.SplitNode - Class in moa.classifiers.trees
ORTO.SplitNode(InstanceConditionalTest, int) - Constructor for class moa.classifiers.trees.ORTO.SplitNode
oScoreKOption - Variable in class moa.clusterers.outliers.AnyOut.AnyOutCore
OutlierAlgoPanel - Class in moa.gui.outliertab
OutlierAlgoPanel() - Constructor for class moa.gui.outliertab.OutlierAlgoPanel
OutlierEvalPanel - Class in moa.gui.outliertab
OutlierEvalPanel() - Constructor for class moa.gui.outliertab.OutlierEvalPanel: Creates new form ClusteringEvalPanel
outlierNotifier - Variable in class moa.clusterers.outliers.MyBaseOutlierDetector
OutlierPanel - Class in moa.gui.visualization
OutlierPanel(MyBaseOutlierDetector, MyBaseOutlierDetector.Outlier, SphereCluster, Color, StreamOutlierPanel) - Constructor for class moa.gui.visualization.OutlierPanel: Creates new form ObjectPanel
OutlierPerformance - Class in moa.evaluation
OutlierPerformance() - Constructor for class moa.evaluation.OutlierPerformance
OutlierSetupTab - Class in moa.gui.outliertab
OutlierSetupTab() - Constructor for class moa.gui.outliertab.OutlierSetupTab: Creates new form outlierSetupTab
OutlierTabPanel - Class in moa.gui.outliertab
OutlierTabPanel() - Constructor for class moa.gui.outliertab.OutlierTabPanel: Creates new form ClusterTab
OutlierVisualEvalPanel - Class in moa.gui.outliertab
OutlierVisualEvalPanel() - Constructor for class moa.gui.outliertab.OutlierVisualEvalPanel: Creates new form OutlierEvalPanel
OutlierVisualTab - Class in moa.gui.outliertab
OutlierVisualTab() - Constructor for class moa.gui.outliertab.OutlierVisualTab: Creates new form OutlierVisualTab
outputCodesOption - Variable in class moa.classifiers.meta.LeveragingBag
outputCodesOption - Variable in class moa.classifiers.meta.OzaBoostAdwin
outputFileOption - Variable in class moa.tasks.MainTask: File option to save the final result of the task to.
outputPredictionFileOption - Variable in class moa.tasks.EvaluateModel
outputPredictionFileOption - Variable in class moa.tasks.EvaluateModelRegression
outputPredictionFileOption - Variable in class moa.tasks.EvaluatePrequential
outputPredictionFileOption - Variable in class moa.tasks.EvaluatePrequentialRegression
outputTypeOption - Variable in class moa.tasks.Plot: Gnuplot terminal - postscript, png, pdf etc.
overlapRadiusDegree(SphereCluster) - Method in class moa.cluster.SphereCluster: Checks whether two SphereCluster overlap based on radius NOTE: overlapRadiusDegree only calculates the overlap based on the centers and the radi, so not the real overlap TODO: should we do this by MC to get the real overlap???
overlapSave(SphereCluster) - Method in class moa.cluster.SphereCluster: When a clusters looses points the new minimal bounding sphere can be partly outside of the originating cluster.
overwriteOldCluster(ClusKernel) - Method in class moa.clusterers.clustree.ClusKernel: Overwrites the LS, SS and weightedN in this cluster to the values of the given cluster but adds N and classCount of the given cluster to this one.
overwriteOldEntry(Entry) - Method in class moa.clusterers.clustree.Entry: Overwrites the LS, SS and weightedN in the data cluster of this Entry to the values of the data cluster in the given Entry, but adds N and classCount of the cluster in the given Entry to the data cluster in this one.
owner(Rule) - Method in class moa.classifiers.rules.core.Rule.Builder
owner - Variable in class moa.classifiers.rules.core.RuleActiveLearningNode
OzaBag - Class in moa.classifiers.meta: Incremental on-line bagging of Oza and Russell.
OzaBag() - Constructor for class moa.classifiers.meta.OzaBag
OzaBagAdwin - Class in moa.classifiers.meta: Bagging for evolving data streams using ADWIN.
OzaBagAdwin() - Constructor for class moa.classifiers.meta.OzaBagAdwin
OzaBagASHT - Class in moa.classifiers.meta: Bagging using trees of different size.
OzaBagASHT() - Constructor for class moa.classifiers.meta.OzaBagASHT
OzaBoost - Class in moa.classifiers.meta: Incremental on-line boosting of Oza and Russell.
OzaBoost() - Constructor for class moa.classifiers.meta.OzaBoost
OzaBoostAdwin - Class in moa.classifiers.meta: Boosting for evolving data streams using ADWIN.
OzaBoostAdwin() - Constructor for class moa.classifiers.meta.OzaBoostAdwin

P

p - Variable in class moa.evaluation.CMM_GTAnalysis.CMMPoint: Reference to original point
pack(byte[]) - Static method in class moa.clusterers.streamkm.MTRandom: This simply utility method can be used in cases where a byte array of seed data is to be used to repeatedly re-seed the random number sequence.
pageHinckleyAlphaOption - Variable in class moa.classifiers.rules.AbstractAMRules
PageHinckleyAlphaOption - Variable in class moa.classifiers.trees.FIMTDD
PageHinckleyAlphaOption - Variable in class moa.classifiers.trees.ORTO
pageHinckleyTest - Variable in class moa.classifiers.rules.core.RuleActiveLearningNode
PageHinckleyTest(double, double) - Method in class moa.classifiers.trees.FIMTDD.Node: Check to see if the tree needs updating
PageHinckleyTest(double, double) - Method in class moa.classifiers.trees.ORTO.InnerNode: Check to see if the tree needs updating
pageHinckleyThresholdOption - Variable in class moa.classifiers.rules.AbstractAMRules
PageHinckleyThresholdOption - Variable in class moa.classifiers.trees.FIMTDD
PageHinckleyThresholdOption - Variable in class moa.classifiers.trees.ORTO
PageHinkleyDM - Class in moa.classifiers.core.driftdetection: Drift detection method based in Page Hinkley Test.
PageHinkleyDM() - Constructor for class moa.classifiers.core.driftdetection.PageHinkleyDM
PageHinkleyFading - Class in moa.classifiers.rules.driftdetection
PageHinkleyFading(double, double) - Constructor for class moa.classifiers.rules.driftdetection.PageHinkleyFading
PageHinkleyTest - Class in moa.classifiers.rules.driftdetection
PageHinkleyTest(double, double) - Constructor for class moa.classifiers.rules.driftdetection.PageHinkleyTest
paint(Graphics) - Method in class moa.gui.LineGraphViewPanel.PlotPanel
paintComponent(Graphics) - Method in class moa.gui.clustertab.ClusteringVisualEvalPanel
paintComponent(Graphics) - Method in class moa.gui.outliertab.OutlierVisualEvalPanel
paintComponent(Graphics) - Method in class moa.gui.visualization.ClusterPanel
paintComponent(Graphics) - Method in class moa.gui.visualization.GraphAxes
paintComponent(Graphics) - Method in class moa.gui.visualization.GraphCanvas
paintComponent(Graphics) - Method in class moa.gui.visualization.GraphCurve
paintComponent(Graphics) - Method in class moa.gui.visualization.OutlierPanel
paintComponent(Graphics) - Method in class moa.gui.visualization.PointPanel
paintValue(Graphics, Rectangle) - Method in class weka.gui.MOAClassOptionEditor: Paints a representation of the current Object.
Pair<T> - Class in moa.clusterers.outliers.utils.mtree.utils: A pair of objects of the same type.
Pair() - Constructor for class moa.clusterers.outliers.utils.mtree.utils.Pair: Creates a pair of null objects.
Pair(T, T) - Constructor for class moa.clusterers.outliers.utils.mtree.utils.Pair: Creates a pair with the objects specified in the arguments.
Pair<T extends Comparable<T>,U extends Comparable<U>> - Class in moa.recommender.rc.utils
Pair(T, U) - Constructor for class moa.recommender.rc.utils.Pair
panel_size - Variable in class moa.gui.visualization.ClusterPanel
panel_size - Variable in class moa.gui.visualization.OutlierPanel
panel_size - Variable in class moa.gui.visualization.PointPanel
parameterOption - Variable in class moa.clusterers.WekaClusteringAlgorithm
parent - Variable in class moa.classifiers.trees.FIMTDD.Node
parent - Variable in class moa.classifiers.trees.HoeffdingOptionTree.FoundNode
parent - Variable in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
parent - Variable in class moa.classifiers.trees.HoeffdingTree.FoundNode
parent - Variable in class moa.classifiers.trees.ORTO.Node
parentBranch - Variable in class moa.classifiers.trees.HoeffdingOptionTree.FoundNode
parentBranch - Variable in class moa.classifiers.trees.HoeffdingTree.FoundNode
partition(Instances, int[], int, int, int) - Static method in class moa.classifiers.lazy.neighboursearch.kdtrees.KMeansInpiredMethod: Partitions the instances around a pivot.
partition(int, int[], int, int) - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.MedianOfWidestDimension: Partitions the instances around a pivot.
partition(double[], double[], int, int) - Static method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch: Partitions the instances around a pivot.
PartitionFunction<DATA> - Interface in moa.clusterers.outliers.utils.mtree: An object with partitions a set of data into two sub-sets.
PartitionFunctions - Class in moa.clusterers.outliers.utils.mtree: Some pre-defined implementations of partition functions.
PartitionFunctions.BalancedPartition<DATA> - Class in moa.clusterers.outliers.utils.mtree: A partition function that tries to distribute the data objects equally between the promoted data objects, associating to each promoted data objects the nearest data objects.
PartitionFunctions.BalancedPartition() - Constructor for class moa.clusterers.outliers.utils.mtree.PartitionFunctions.BalancedPartition
partitions - Variable in class moa.clusterers.outliers.utils.mtree.SplitFunction.SplitResult: A pair of partitions corresponding to the promoted data objects.
pause() - Static method in class moa.gui.visualization.RunOutlierVisualizer
pause() - Static method in class moa.gui.visualization.RunVisualizer
pauseFlag - Variable in class moa.tasks.StandardTaskMonitor
pauseSelectedTasks() - Method in class moa.gui.conceptdrift.CDTaskManagerPanel
pauseSelectedTasks() - Method in class moa.gui.RegressionTaskManagerPanel
pauseSelectedTasks() - Method in class moa.gui.TaskManagerPanel
pauseTask() - Method in class moa.tasks.TaskThread
pauseTaskButton - Variable in class moa.gui.conceptdrift.CDTaskManagerPanel
pauseTaskButton - Variable in class moa.gui.RegressionTaskManagerPanel
pauseTaskButton - Variable in class moa.gui.TaskManagerPanel
peek() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.MyHeap: peeks at the first element.
penaltyFactorOption - Variable in class moa.classifiers.meta.LimAttClassifier
Perceptron - Class in moa.classifiers.functions: Single perceptron classifier.
Perceptron() - Constructor for class moa.classifiers.functions.Perceptron
perceptron - Variable in class moa.classifiers.rules.core.RuleActiveRegressionNode
Perceptron - Class in moa.classifiers.rules.functions
Perceptron() - Constructor for class moa.classifiers.rules.functions.Perceptron
Perceptron(Perceptron) - Constructor for class moa.classifiers.rules.functions.Perceptron
perceptronattributeStatistics - Variable in class moa.classifiers.rules.functions.Perceptron
perceptronInstancesSeen - Variable in class moa.classifiers.rules.functions.Perceptron
perceptronsumY - Variable in class moa.classifiers.rules.functions.Perceptron
perceptronYSeen - Variable in class moa.classifiers.rules.functions.Perceptron
period - Variable in class moa.streams.generators.cd.AbstractConceptDriftGenerator
perturbValue(double, double, double) - Method in class moa.streams.generators.AgrawalGenerator
perturbValue(double, double, double, double) - Method in class moa.streams.generators.AgrawalGenerator
peturbFractionOption - Variable in class moa.streams.generators.AgrawalGenerator
phinstancesSeen - Variable in class moa.classifiers.rules.driftdetection.PageHinkleyTest
PHmin - Variable in class moa.classifiers.trees.FIMTDD.Node
PHmT - Variable in class moa.classifiers.rules.RuleClassification
PHMT - Variable in class moa.classifiers.rules.RuleClassification
PHmT - Variable in class moa.classifiers.trees.ORTO.ActiveLearningNode
PHMT - Variable in class moa.classifiers.trees.ORTO.ActiveLearningNode
PHmT - Variable in class moa.classifiers.trees.ORTO.InnerNode
PHMT - Variable in class moa.classifiers.trees.ORTO.InnerNode
PHsum - Variable in class moa.classifiers.trees.FIMTDD.Node
pID - Variable in class moa.evaluation.CMM_GTAnalysis.CMMPoint: point ID
pineg - Variable in class moa.classifiers.meta.OCBoost
pipos - Variable in class moa.classifiers.meta.OCBoost
Plot - Class in moa.tasks: A task allowing to create and plot gnuplot scripts.
Plot() - Constructor for class moa.tasks.Plot
Plot.LegendLocation - Enum in moa.tasks: Location of the legend on the plot.
Plot.LegendType - Enum in moa.tasks: Type of legend.
Plot.PlotStyle - Enum in moa.tasks
Plot.Terminal - Enum in moa.tasks: Plot output terminal.
plotLines - Variable in class moa.gui.LineGraphViewPanel
plotOutputOption - Variable in class moa.tasks.Plot: FileOption for selecting the plot output file.
plotStyleOption - Variable in class moa.tasks.Plot: Type of plot - dots, points, lines ets.
PminOption - Variable in class moa.classifiers.rules.RuleClassifier
Point - Class in moa.clusterers.streamkm
Point(int) - Constructor for class moa.clusterers.streamkm.Point
Point(Instance, int) - Constructor for class moa.clusterers.streamkm.Point
pointIntervalOption - Variable in class moa.tasks.Plot: Interval between plotted data points.
PointPanel - Class in moa.gui.visualization
PointPanel(DataPoint, StreamPanel, double, double) - Constructor for class moa.gui.visualization.PointPanel: Type 1: Possibly be decayed, colored by class label.
PointPanel(DataPoint, StreamPanel, Color) - Constructor for class moa.gui.visualization.PointPanel: Type 2: Never be decayed, single color.
poisson(double, Random) - Static method in class moa.core.MiscUtils
pOption - Variable in class moa.clusterers.outliers.Angiulli.ApproxSTORM
positionOffsetOption - Variable in class moa.clusterers.ClusterGenerator
positionOption - Variable in class moa.streams.ConceptDriftRealStream
positionOption - Variable in class moa.streams.ConceptDriftStream
postProcessDistances(double[]) - Method in interface moa.classifiers.lazy.neighboursearch.DistanceFunction: Does post processing of the distances (if necessary) returned by distance(distance(Instance first, Instance second, double cutOffValue).
postProcessDistances(double[]) - Method in class moa.classifiers.lazy.neighboursearch.EuclideanDistance: Does post processing of the distances (if necessary) returned by distance(distance(Instance first, Instance second, double cutOffValue).
postProcessDistances(double[]) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Does nothing, derived classes may override it though.
posWindow - Variable in class moa.evaluation.WindowClassificationPerformanceEvaluator.Estimator
posWindow - Variable in class moa.evaluation.WindowRegressionPerformanceEvaluator.Estimator
preciseThreadTimesAvailable - Static variable in class moa.core.TimingUtils
Predicate - Interface in moa.classifiers.rules.core
Predicates - Class in moa.classifiers.rules
Predicates(double, double, double) - Constructor for class moa.classifiers.rules.Predicates
predicateSet - Variable in class moa.classifiers.rules.RuleClassification
prediction(Instance, int) - Method in class moa.classifiers.functions.Perceptron
prediction(double[][], int) - Method in class moa.classifiers.meta.LimAttClassifier
prediction(double[]) - Method in class moa.classifiers.rules.functions.Perceptron
prediction(DoubleVector) - Method in class moa.classifiers.trees.FIMTDD.FIMTDDPerceptron: Output the prediction made by this perceptron on the given instance
prediction(Instance) - Method in class moa.classifiers.trees.ORTO.ORTOPerceptron: Output the prediction made by this perceptron on the given instance
predictionFunction - Variable in class moa.classifiers.rules.core.Rule.Builder
predictionFunction(int) - Method in class moa.classifiers.rules.core.Rule.Builder
predictionFunction - Variable in class moa.classifiers.rules.core.RuleActiveLearningNode
predictionFunctionOption - Variable in class moa.classifiers.rules.AMRulesRegressor
predictionFunctionOption - Variable in class moa.classifiers.rules.RuleClassifier
predictionOption - Variable in class moa.classifiers.core.driftdetection.EnsembleDriftDetectionMethods
predictionPruning(double[][], int[], int) - Method in class moa.classifiers.meta.LimAttClassifier
predictRating(Integer, Integer) - Method in class moa.recommender.predictor.BaselinePredictor
predictRating(int, int) - Method in class moa.recommender.predictor.BaselinePredictor
predictRating(Integer, Integer) - Method in class moa.recommender.predictor.BRISMFPredictor
predictRating(int, int) - Method in class moa.recommender.predictor.BRISMFPredictor
predictRating(int, int) - Method in interface moa.recommender.predictor.RatingPredictor
predictRating(int, int) - Method in class moa.recommender.rc.predictor.impl.BaselinePredictor
predictRating(int, int) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
predictRating(float[], float[]) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
predictRating(int, int) - Method in interface moa.recommender.rc.predictor.RatingPredictor
predictRatings(int, List<Integer>) - Method in class moa.recommender.predictor.BaselinePredictor
predictRatings(int, List<Integer>) - Method in class moa.recommender.predictor.BRISMFPredictor
predictRatings(int, List<Integer>) - Method in interface moa.recommender.predictor.RatingPredictor
predictRatings(int, List<Integer>) - Method in class moa.recommender.rc.predictor.impl.BaselinePredictor
predictRatings(int, List<Integer>) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
predictRatings(int, List<Integer>) - Method in interface moa.recommender.rc.predictor.RatingPredictor
preds - Variable in class moa.classifiers.core.driftdetection.EnsembleDriftDetectionMethods
prepareClassOptions(TaskMonitor, ObjectRepository) - Method in class moa.options.AbstractOptionHandler: Prepares the options of this class.
prepareForUse() - Method in class moa.options.AbstractOptionHandler
prepareForUse(TaskMonitor, ObjectRepository) - Method in class moa.options.AbstractOptionHandler
prepareForUse() - Method in interface moa.options.OptionHandler: This method prepares this object for use.
prepareForUse(TaskMonitor, ObjectRepository) - Method in interface moa.options.OptionHandler: This method prepares this object for use.
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.AbstractClassifier
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserver
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserverRegression
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.attributeclassobservers.FIMTDDNumericAttributeClassObserver
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.attributeclassobservers.GaussianNumericAttributeClassObserver
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.attributeclassobservers.GreenwaldKhannaNumericAttributeClassObserver
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.attributeclassobservers.NominalAttributeClassObserver
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.attributeclassobservers.NullAttributeClassObserver
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.attributeclassobservers.VFMLNumericAttributeClassObserver
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.driftdetection.ADWINChangeDetector
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.driftdetection.CusumDM
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.driftdetection.DDM
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.driftdetection.EDDM
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.driftdetection.EnsembleDriftDetectionMethods
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.driftdetection.EWMAChartDM
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.driftdetection.GeometricMovingAverageDM
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.driftdetection.HDDM_A_Test
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.driftdetection.HDDM_W_Test
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.driftdetection.PageHinkleyDM
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.driftdetection.SeqDrift1ChangeDetector
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.splitcriteria.GiniSplitCriterion
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.splitcriteria.InfoGainSplitCriterion
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.splitcriteria.VarianceReductionSplitCriterion
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.meta.AccuracyUpdatedEnsemble
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.meta.AccuracyWeightedEnsemble
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.meta.WeightedMajorityAlgorithm
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.clusterers.AbstractClusterer
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.evaluation.EWMAClassificationPerformanceEvaluator
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.evaluation.FadingFactorClassificationPerformanceEvaluator
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.evaluation.WindowClassificationPerformanceEvaluator
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.evaluation.WindowRegressionPerformanceEvaluator
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.options.AbstractOptionHandler: This method describes the implementation of how to prepare this object for use.
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.recommender.data.MemRecommenderData
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.recommender.dataset.impl.FlixsterDataset
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.recommender.dataset.impl.JesterDataset
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.recommender.dataset.impl.MovielensDataset
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.recommender.predictor.BaselinePredictor
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.recommender.predictor.BRISMFPredictor
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.ArffFileStream
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.clustering.FileStream
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.clustering.RandomRBFGeneratorEvents
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.ConceptDriftRealStream
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.ConceptDriftStream
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.FilteredStream
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.filters.AbstractStreamFilter
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.generators.AgrawalGenerator
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.generators.cd.AbstractConceptDriftGenerator
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.generators.HyperplaneGenerator
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.generators.LEDGenerator
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.generators.LEDGeneratorDrift
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.generators.multilabel.MetaMultilabelGenerator
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.generators.RandomRBFGenerator
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.generators.RandomTreeGenerator
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.generators.SEAGenerator
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.generators.STAGGERGenerator
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.generators.WaveformGenerator
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.generators.WaveformGeneratorDrift
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.MultiFilteredStream
prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.tasks.AbstractTask
previewedThread - Variable in class moa.gui.PreviewPanel
previewLabel - Variable in class moa.gui.PreviewPanel
previewPanel - Variable in class moa.gui.ClassificationTabPanel
previewPanel - Variable in class moa.gui.conceptdrift.CDTaskManagerPanel
previewPanel - Variable in class moa.gui.ConceptDriftTabPanel
PreviewPanel - Class in moa.gui: This panel displays the running task preview text and buttons.
PreviewPanel() - Constructor for class moa.gui.PreviewPanel
PreviewPanel(PreviewPanel.TypePanel) - Constructor for class moa.gui.PreviewPanel
PreviewPanel(PreviewPanel.TypePanel, CDTaskManagerPanel) - Constructor for class moa.gui.PreviewPanel
previewPanel - Variable in class moa.gui.RegressionTabPanel
previewPanel - Variable in class moa.gui.RegressionTaskManagerPanel
previewPanel - Variable in class moa.gui.TaskLauncher
previewPanel - Variable in class moa.gui.TaskManagerPanel
PreviewPanel.TypePanel - Enum in moa.gui
previousWeight - Variable in class moa.classifiers.trees.FIMTDD.SplitNode
previousWeight - Variable in class moa.classifiers.trees.ORTO.InnerNode
Print(String) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
print(String) - Method in interface moa.clusterers.outliers.MyBaseOutlierDetector.PrintMsg
print(String) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector.StdPrintMsg
Print_lt_cnt(ArrayList<Integer>) - Method in class moa.clusterers.outliers.AbstractC.AbstractCBase
printAnomaliesSupervised(StringBuilder, int) - Method in class moa.classifiers.rules.RuleClassifier
printAnomaliesUnsupervised(StringBuilder, int) - Method in class moa.classifiers.rules.RuleClassifier
PrintEventQueue() - Method in class moa.clusterers.outliers.MCOD.MCODBase
PrintEventQueue() - Method in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
Printf(String, Object...) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
printf(String, Object...) - Method in interface moa.clusterers.outliers.MyBaseOutlierDetector.PrintMsg
printf(String, Object...) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector.StdPrintMsg
PrintInstance(Instance) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
PrintISB() - Method in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
printList() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborList: Prints out the contents of the neighborlist.
Println(String) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
println(String) - Method in interface moa.clusterers.outliers.MyBaseOutlierDetector.PrintMsg
println(String) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector.StdPrintMsg
PrintMCSet(Set<MicroCluster>) - Method in class moa.clusterers.outliers.MCOD.MCODBase
PrintNodeList(List<ISBIndex.ISBNode>) - Method in class moa.clusterers.outliers.MCOD.MCODBase
PrintNodeList(List<ISBIndex.ISBNode>) - Method in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
PrintNodeSet(Set<ISBIndex.ISBNode>) - Method in class moa.clusterers.outliers.MCOD.MCODBase
PrintNodeSet(Set<ISBIndex.ISBNode>) - Method in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
PrintNodeVector(Vector<ISBIndex.ISBNode>) - Method in class moa.clusterers.outliers.MCOD.MCODBase
PrintNodeVector(Vector<ISBIndex.ISBNode>) - Method in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
PrintOutliers() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
PrintPD() - Method in class moa.clusterers.outliers.MCOD.MCODBase
PrintPrecNeighs() - Method in class moa.clusterers.outliers.Angiulli.ExactSTORM.ISBNodeExact
printRule() - Method in class moa.classifiers.rules.core.Rule
PrintRuleSet() - Method in class moa.classifiers.rules.AbstractAMRules
priors - Variable in class moa.streams.generators.multilabel.MetaMultilabelGenerator
priors_norm - Variable in class moa.streams.generators.multilabel.MetaMultilabelGenerator
prob - Variable in class moa.classifiers.lazy.kNNwithPAW
prob - Variable in class moa.classifiers.lazy.kNNwithPAWandADWIN
probabilityDensity(double) - Method in class moa.core.GaussianEstimator
probabilityOfAttributeValueGivenClass(double, int) - Method in interface moa.classifiers.core.attributeclassobservers.AttributeClassObserver: Gets the probability for an attribute value given a class
probabilityOfAttributeValueGivenClass(double, int) - Method in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserver
probabilityOfAttributeValueGivenClass(double, int) - Method in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserverRegression
probabilityOfAttributeValueGivenClass(double, int) - Method in class moa.classifiers.core.attributeclassobservers.FIMTDDNumericAttributeClassObserver
probabilityOfAttributeValueGivenClass(double, int) - Method in class moa.classifiers.core.attributeclassobservers.GaussianNumericAttributeClassObserver
probabilityOfAttributeValueGivenClass(double, int) - Method in class moa.classifiers.core.attributeclassobservers.GreenwaldKhannaNumericAttributeClassObserver
probabilityOfAttributeValueGivenClass(double, int) - Method in class moa.classifiers.core.attributeclassobservers.NominalAttributeClassObserver
probabilityOfAttributeValueGivenClass(double, int) - Method in class moa.classifiers.core.attributeclassobservers.NullAttributeClassObserver
probabilityOfAttributeValueGivenClass(double, int) - Method in class moa.classifiers.core.attributeclassobservers.VFMLNumericAttributeClassObserver
probabilityThresholdOption - Variable in class moa.classifiers.rules.RuleClassifier
process(Set<DATA>, DistanceFunction<? super DATA>) - Method in class moa.clusterers.outliers.utils.mtree.ComposedSplitFunction
process(Pair<DATA>, Set<DATA>, DistanceFunction<? super DATA>) - Method in interface moa.clusterers.outliers.utils.mtree.PartitionFunction: Executes the partitioning.
process(Pair<DATA>, Set<DATA>, DistanceFunction<? super DATA>) - Method in class moa.clusterers.outliers.utils.mtree.PartitionFunctions.BalancedPartition: Processes the balanced partition.
process(Set<DATA>, DistanceFunction<? super DATA>) - Method in interface moa.clusterers.outliers.utils.mtree.PromotionFunction: Chooses (promotes) a pair of objects according to some criteria that is suitable for the application using the M-Tree.
process(Set<DATA>, DistanceFunction<? super DATA>) - Method in class moa.clusterers.outliers.utils.mtree.PromotionFunctions.RandomPromotion
process(Set<DATA>, DistanceFunction<? super DATA>) - Method in interface moa.clusterers.outliers.utils.mtree.SplitFunction: Processes the splitting of a node.
processChunk() - Method in class moa.classifiers.meta.AccuracyUpdatedEnsemble: Processes a chunk of instances.
processChunk() - Method in class moa.classifiers.meta.AccuracyWeightedEnsemble: Processes a chunk.
processedInstances - Variable in class moa.classifiers.meta.AccuracyUpdatedEnsemble: Number of processed examples.
processedInstances - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble
processedInstances - Variable in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble: Number of processed examples.
processingSpeed - Variable in class moa.clusterers.denstream.WithDBSCAN
processInstance(Instance, FIMTDD.Node, double, double, boolean, boolean) - Method in class moa.classifiers.trees.FIMTDD
processInstance(Instance, ORTO) - Method in class moa.classifiers.trees.ORTO.ActiveLearningNode
processInstance(Instance, ORTO) - Method in class moa.classifiers.trees.ORTO.Node
processInstance(Instance, ORTO) - Method in class moa.classifiers.trees.ORTO.OptionNode
processInstance(Instance, ORTO) - Method in class moa.classifiers.trees.ORTO.SplitNode
processNewInstanceImpl(Instance) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
ProcessNewStreamObj(Instance) - Method in class moa.clusterers.outliers.AbstractC.AbstractC
ProcessNewStreamObj(Instance) - Method in class moa.clusterers.outliers.Angiulli.ApproxSTORM
ProcessNewStreamObj(Instance) - Method in class moa.clusterers.outliers.Angiulli.ExactSTORM
ProcessNewStreamObj(Instance) - Method in class moa.clusterers.outliers.AnyOut.AnyOut
ProcessNewStreamObj(Instance) - Method in class moa.clusterers.outliers.MCOD.MCOD
ProcessNewStreamObj(Instance) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
ProcessNewStreamObj(Instance) - Method in class moa.clusterers.outliers.SimpleCOD.SimpleCOD
progressAnimSequence - Static variable in class moa.DoTask: Array of characters to use to animate the progress of tasks running.
promoted - Variable in class moa.clusterers.outliers.utils.mtree.SplitFunction.SplitResult: A pair of promoted data objects.
PromotionFunction<DATA> - Interface in moa.clusterers.outliers.utils.mtree: An object that chooses a pair from a set of data objects.
PromotionFunctions - Class in moa.clusterers.outliers.utils.mtree: Some pre-defined implementations of promotion functions.
PromotionFunctions.RandomPromotion<DATA> - Class in moa.clusterers.outliers.utils.mtree: A promotion function object that randomly chooses ("promotes") two data objects.
PromotionFunctions.RandomPromotion() - Constructor for class moa.clusterers.outliers.utils.mtree.PromotionFunctions.RandomPromotion
PROPERTIES - Static variable in class moa.gui.GUIDefaults: Properties associated with the GUI options.
PropertiesReader - Class in moa.core: Class implementing some properties reader utility methods.
PropertiesReader() - Constructor for class moa.core.PropertiesReader
PROPERTY_FILE - Static variable in class moa.gui.GUIDefaults: The name of the properties file.
prunedAlternateTrees - Variable in class moa.classifiers.trees.HoeffdingAdaptiveTree
pruneOption - Variable in class moa.classifiers.meta.LimAttClassifier
pruneOption - Variable in class moa.classifiers.meta.WeightedMajorityAlgorithm
pruneToK(int) - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborList: Prunes the list to contain the k nearest neighbors.
pureBoostOption - Variable in class moa.classifiers.meta.OzaBoost
pureBoostOption - Variable in class moa.classifiers.meta.OzaBoostAdwin
purpose - Variable in class moa.options.AbstractOption: Text of the purpose of this option.
put(int, double) - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.MyHeap: adds the value to the heap.
putBySubstitute(int, double) - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.MyHeap: Puts an element by substituting it in place of the top most element.
putKthNearest(int, double) - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.MyHeap: Stores kth nearest elements (if there are more than one).

Q

queryFreqOption - Variable in class moa.clusterers.outliers.Angiulli.ApproxSTORM
queryFreqOption - Variable in class moa.clusterers.outliers.Angiulli.ExactSTORM
quickSort(Instances, int[], int, int, int) - Static method in class moa.classifiers.lazy.neighboursearch.kdtrees.KMeansInpiredMethod: Sorts the instances according to the given attribute/dimension.
quickSort(double[], double[], int, int) - Static method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch: performs quicksort.

R

R_MAX - Static variable in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Index in ranges for MAX.
R_MIN - Static variable in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Index in ranges for MIN.
R_WIDTH - Static variable in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Index in ranges for WIDTH.
radius() - Method in class moa.cluster.Miniball: Return the Radius of the miniball
radiusDecreaseOption - Variable in class moa.clusterers.ClusterGenerator
radiusFactor - Variable in class moa.cluster.CFCluster
radiusIncreaseOption - Variable in class moa.clusterers.ClusterGenerator
radiusOption - Variable in class moa.clusterers.outliers.AbstractC.AbstractC
radiusOption - Variable in class moa.clusterers.outliers.Angiulli.ApproxSTORM
radiusOption - Variable in class moa.clusterers.outliers.Angiulli.ExactSTORM
radiusOption - Variable in class moa.clusterers.outliers.MCOD.MCOD
radiusOption - Variable in class moa.clusterers.outliers.SimpleCOD.SimpleCOD
random - Variable in class moa.clusterers.outliers.MyBaseOutlierDetector
random - Variable in class moa.streams.ConceptDriftRealStream
random - Variable in class moa.streams.ConceptDriftStream
random - Variable in class moa.streams.filters.AddNoiseFilter
RandomHoeffdingTree - Class in moa.classifiers.trees: Random decision trees for data streams.
RandomHoeffdingTree() - Constructor for class moa.classifiers.trees.RandomHoeffdingTree
RandomHoeffdingTree.LearningNodeNB - Class in moa.classifiers.trees
RandomHoeffdingTree.LearningNodeNB(double[]) - Constructor for class moa.classifiers.trees.RandomHoeffdingTree.LearningNodeNB
RandomHoeffdingTree.LearningNodeNBAdaptive - Class in moa.classifiers.trees
RandomHoeffdingTree.LearningNodeNBAdaptive(double[]) - Constructor for class moa.classifiers.trees.RandomHoeffdingTree.LearningNodeNBAdaptive
RandomHoeffdingTree.RandomLearningNode - Class in moa.classifiers.trees
RandomHoeffdingTree.RandomLearningNode(double[]) - Constructor for class moa.classifiers.trees.RandomHoeffdingTree.RandomLearningNode
RandomRBFGenerator - Class in moa.streams.generators: Stream generator for a random radial basis function stream.
RandomRBFGenerator() - Constructor for class moa.streams.generators.RandomRBFGenerator
RandomRBFGenerator.Centroid - Class in moa.streams.generators
RandomRBFGenerator.Centroid() - Constructor for class moa.streams.generators.RandomRBFGenerator.Centroid
RandomRBFGeneratorDrift - Class in moa.streams.generators: Stream generator for a random radial basis function stream with drift.
RandomRBFGeneratorDrift() - Constructor for class moa.streams.generators.RandomRBFGeneratorDrift
RandomRBFGeneratorEvents - Class in moa.streams.clustering
RandomRBFGeneratorEvents() - Constructor for class moa.streams.clustering.RandomRBFGeneratorEvents
RandomRules - Class in moa.classifiers.meta
RandomRules() - Constructor for class moa.classifiers.meta.RandomRules
randomSample(Collection<T>, int) - Static method in class moa.clusterers.outliers.utils.mtree.utils.Utils: Randomly chooses elements from the collection.
randomSeed - Variable in class moa.classifiers.AbstractClassifier: Random seed used in randomizable learners
randomSeed - Variable in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaLearningNode
randomSeed - Variable in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaSplitNode
randomSeed - Variable in class moa.clusterers.AbstractClusterer
randomSeedOption - Variable in class moa.classifiers.AbstractClassifier: Option for randomizable learners to change the random seed
randomSeedOption - Variable in class moa.clusterers.AbstractClusterer
randomSeedOption - Variable in class moa.clusterers.CobWeb
randomSeedOption - Variable in class moa.clusterers.streamkm.StreamKM
randomSeedOption - Variable in class moa.streams.ConceptDriftRealStream
randomSeedOption - Variable in class moa.streams.ConceptDriftStream
randomSeedOption - Variable in class moa.streams.filters.AddNoiseFilter
randomSeedOption - Variable in class moa.tasks.EvaluateInterleavedTestThenTrain
RandomTreeGenerator - Class in moa.streams.generators: Stream generator for a stream based on a randomly generated tree..
RandomTreeGenerator() - Constructor for class moa.streams.generators.RandomTreeGenerator
RandomTreeGenerator.Node - Class in moa.streams.generators
RandomTreeGenerator.Node() - Constructor for class moa.streams.generators.RandomTreeGenerator.Node
RangeSearch(ISBIndex.ISBNode, double) - Method in class moa.clusterers.outliers.AbstractC.ISBIndex
RangeSearch(ISBIndex.ISBNode, double) - Method in class moa.clusterers.outliers.Angiulli.ISBIndex
RangeSearch(ISBIndex.ISBNode, double) - Method in class moa.clusterers.outliers.MCOD.ISBIndex
RangeSearch(ISBIndex.ISBNode, double) - Method in class moa.clusterers.outliers.SimpleCOD.ISBIndex
rangesSet() - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Check if ranges are set.
Rating - Class in moa.recommender.rc.utils
Rating(int, int, double) - Constructor for class moa.recommender.rc.utils.Rating
rating - Variable in class moa.recommender.rc.utils.Rating
ratingIterator() - Method in class moa.recommender.rc.data.impl.MemRecommenderData
ratingIterator() - Method in interface moa.recommender.rc.data.RecommenderData
RatingPredictor - Interface in moa.recommender.predictor: Rating predicting algorithm.
RatingPredictor - Interface in moa.recommender.rc.predictor
ratingPredictorOption - Variable in class moa.tasks.EvaluateOnlineRecommender
ratingsItem - Variable in class moa.recommender.rc.data.impl.MemRecommenderData
ratingsUser - Variable in class moa.recommender.rc.data.impl.MemRecommenderData
read() - Method in class moa.core.InputStreamProgressMonitor
read(byte[]) - Method in class moa.core.InputStreamProgressMonitor
read(byte[], int, int) - Method in class moa.core.InputStreamProgressMonitor
readFromFile(File) - Static method in class moa.core.SerializeUtils
readInstance(Reader) - Method in class moa.core.InstancesHeader
readMinMaxDiffValues(HashSet<Integer>) - Method in class moa.streams.clustering.FileStream
readNextInstanceFromFile() - Method in class moa.streams.ArffFileStream
readNextInstanceFromFile() - Method in class moa.streams.clustering.FileStream
readProperties(String) - Static method in class moa.core.PropertiesReader: Reads properties that inherit from three locations.
rearrangePoints(int[], int, int, int, double) - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KMeansInpiredMethod: Re-arranges the indices array so that in the portion of the array belonging to the node to be split, the points <= to the splitVal are on the left of the portion and those > the splitVal are on the right.
rearrangePoints(int[], int, int, int, double) - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.MidPointOfWidestDimension: Re-arranges the indices array such that the points <= to the splitVal are on the left of the array and those > the splitVal are on the right.
rearrangePoints(int[], int, int, int, double) - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.SlidingMidPointOfWidestSide: Re-arranges the indices array such that the points <= to the splitVal are on the left of the array and those > the splitVal are on the right.
recalculateData() - Method in class moa.clusterers.clustree.Entry: This functions reads every entry in the child node and calculates the corresponding data Kernel.
recentChunk - Variable in class moa.classifiers.meta.ADACC: Last chunk of data of size (tau_size) to compute the stability index
RecommenderData - Interface in moa.recommender.data
RecommenderData - Interface in moa.recommender.rc.data
RedirectToDisplay() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector.StdPrintMsg
RedirectToFile(String) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector.StdPrintMsg
RedirectToFile() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector.StdPrintMsg
redraw() - Method in class moa.gui.visualization.RunOutlierVisualizer
redraw() - Method in class moa.gui.visualization.RunVisualizer
redrawOnResize() - Method in class moa.gui.visualization.RunOutlierVisualizer
RedrawPointLayer() - Method in class moa.gui.visualization.StreamOutlierPanel
refineOwners(KDTreeNode, Instances, int[]) - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Refines the ownerlist.
refresh() - Method in class moa.gui.PreviewPanel
refreshButton - Variable in class moa.gui.PreviewPanel
RegressionAccuracy - Class in moa.evaluation
RegressionAccuracy() - Constructor for class moa.evaluation.RegressionAccuracy
RegressionMainTask - Class in moa.tasks
RegressionMainTask() - Constructor for class moa.tasks.RegressionMainTask
RegressionPerformanceEvaluator - Interface in moa.evaluation: Interface implemented by learner evaluators to monitor the results of the regression learning process.
RegressionTabPanel - Class in moa.gui: This panel allows the user to select and configure a task, and run it.
RegressionTabPanel() - Constructor for class moa.gui.RegressionTabPanel
RegressionTaskManagerPanel - Class in moa.gui: This panel displays the running tasks.
RegressionTaskManagerPanel() - Constructor for class moa.gui.RegressionTaskManagerPanel
RegressionTaskManagerPanel.ProgressCellRenderer - Class in moa.gui
RegressionTaskManagerPanel.ProgressCellRenderer() - Constructor for class moa.gui.RegressionTaskManagerPanel.ProgressCellRenderer
RegressionTaskManagerPanel.TaskTableModel - Class in moa.gui
RegressionTaskManagerPanel.TaskTableModel() - Constructor for class moa.gui.RegressionTaskManagerPanel.TaskTableModel
regressionTreeOption - Variable in class moa.classifiers.trees.FIMTDD
Regressor - Interface in moa.classifiers: Regressor interface for incremental regression models.
remove(int) - Method in class moa.cluster.Clustering: remove a cluster from the clustering
remove(CFCluster) - Method in class moa.clusterers.macro.NonConvexCluster
Remove(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.AbstractC.ISBIndex
Remove(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.Angiulli.ISBIndex
Remove(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.MCOD.ISBIndex
Remove(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.SimpleCOD.ISBIndex
remove(DATA) - Method in class moa.clusterers.outliers.utils.mtree.MTree: Removes a data object from the M-Tree.
remove(int) - Method in class moa.core.AutoExpandVector
remove(Object) - Method in class moa.core.AutoExpandVector
remove() - Method in class moa.recommender.rc.data.impl.MemRecommenderData.RatingIterator
remove() - Method in class moa.recommender.rc.utils.DenseVector.DenseVectorIterator
remove(int) - Method in class moa.recommender.rc.utils.DenseVector
remove(int) - Method in class moa.recommender.rc.utils.SparseVector
remove() - Method in class moa.recommender.rc.utils.SparseVector.SparseVectorIterator
remove(int) - Method in class moa.recommender.rc.utils.Vector
removeAllOptions() - Method in class moa.options.Options
removeAttributesOption - Variable in class moa.streams.clustering.FileStream
removeBadSplits(SplitCriterion, double, double, double) - Method in class moa.classifiers.core.attributeclassobservers.FIMTDDNumericAttributeClassObserver: A method to remove all nodes in the E-BST in which it and all it's children represent 'bad' split points
removeChangeListener(ChangeListener) - Method in class moa.gui.ClassOptionEditComponent: Removes the listener from the internal set of listeners.
removeChangeListener(ChangeListener) - Method in class moa.gui.ClassOptionWithNamesEditComponent: Removes the listener from the internal set of listeners.
removeClusterChangeListener(ClusterEventListener) - Method in class moa.streams.clustering.RandomRBFGeneratorEvents: Remove a listener
removeExcessTrees() - Method in class moa.classifiers.trees.ORTO
RemoveExpiredOutlier(MyBaseOutlierDetector.Outlier) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
removeItem(int) - Method in class moa.recommender.rc.data.AbstractRecommenderData
removeItem(int) - Method in class moa.recommender.rc.data.impl.MemRecommenderData
removeItem(int) - Method in interface moa.recommender.rc.data.RecommenderData
RemoveNode(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.MCOD.MicroCluster
removeObject(int) - Method in class moa.clusterers.outliers.AnyOut.AnyOutCore
removeOption(String) - Method in class moa.options.Options
removeOption(Option) - Method in class moa.options.Options
RemoveOutlier(MyBaseOutlierDetector.Outlier) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
removePoorAttsOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree
removePoorAttsOption - Variable in class moa.classifiers.trees.HoeffdingTree
removePoorAttsOption - Variable in class moa.classifiers.trees.ORTO
removePoorestModelBytes() - Method in class moa.classifiers.meta.AccuracyWeightedEnsemble: Removes the poorest classifier from the model, thus decreasing the models size.
removePoorestModelBytes() - Method in class moa.classifiers.meta.WeightedMajorityAlgorithm
RemovePrecNeigh(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
RemovePrecNeigh(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBNode
removeRange(int, int) - Method in class moa.core.AutoExpandVector
removeRating(int, int) - Method in class moa.recommender.rc.data.AbstractRecommenderData
removeRating(int, int) - Method in class moa.recommender.rc.data.impl.MemRecommenderData
removeRating(int, int) - Method in interface moa.recommender.rc.data.RecommenderData
removeTaskCompletionListener(TaskCompletionListener) - Method in class moa.tasks.TaskThread
removeUser(int) - Method in class moa.recommender.rc.data.AbstractRecommenderData
removeUser(int) - Method in class moa.recommender.rc.data.impl.MemRecommenderData
removeUser(int) - Method in interface moa.recommender.rc.data.RecommenderData
renderAlgoPanel() - Method in class moa.gui.clustertab.ClusteringAlgoPanel
renderAlgoPanel() - Method in class moa.gui.outliertab.OutlierAlgoPanel
renderAWTBox(Graphics, int, int, int, int) - Method in interface moa.gui.AWTRenderer
repaint() - Method in class moa.gui.clustertab.ClusteringVisualTab
repaint() - Method in class moa.gui.outliertab.OutlierVisualTab
repaintOutliers() - Method in class moa.gui.visualization.StreamOutlierPanel
ReplacingMissingValuesFilter - Class in moa.streams.filters: Replaces the missing values with another value according to the selected strategy.
ReplacingMissingValuesFilter() - Constructor for class moa.streams.filters.ReplacingMissingValuesFilter
ReplacingMissingValuesFilter.MapUtil - Class in moa.streams.filters
ReplacingMissingValuesFilter.MapUtil() - Constructor for class moa.streams.filters.ReplacingMissingValuesFilter.MapUtil
repository - Variable in class moa.tasks.TaskThread
requestCancel() - Method in class moa.tasks.NullMonitor
requestCancel() - Method in class moa.tasks.StandardTaskMonitor
requestCancel() - Method in interface moa.tasks.TaskMonitor: Requests the task monitored to cancel.
requestPause() - Method in class moa.tasks.NullMonitor
requestPause() - Method in class moa.tasks.StandardTaskMonitor
requestPause() - Method in interface moa.tasks.TaskMonitor: Requests the task monitored to pause.
requestResultPreview() - Method in class moa.tasks.NullMonitor
requestResultPreview(ResultPreviewListener) - Method in class moa.tasks.NullMonitor
requestResultPreview() - Method in class moa.tasks.StandardTaskMonitor
requestResultPreview(ResultPreviewListener) - Method in class moa.tasks.StandardTaskMonitor
requestResultPreview() - Method in interface moa.tasks.TaskMonitor: Requests to preview the task result.
requestResultPreview(ResultPreviewListener) - Method in interface moa.tasks.TaskMonitor: Requests to preview the task result.
requestResume() - Method in class moa.tasks.NullMonitor
requestResume() - Method in class moa.tasks.StandardTaskMonitor
requestResume() - Method in interface moa.tasks.TaskMonitor: Requests the task monitored to resume.
RequiredOptionNotSpecifiedException - Exception in moa.options
RequiredOptionNotSpecifiedException() - Constructor for exception moa.options.RequiredOptionNotSpecifiedException
requiredType - Variable in class moa.options.AbstractClassOption: The class type
reset - Variable in class moa.classifiers.bayes.NaiveBayesMultinomial
reset - Variable in class moa.classifiers.functions.Perceptron
reset() - Method in class moa.classifiers.functions.SGD: Reset the classifier.
reset() - Method in class moa.classifiers.functions.SGDMultiClass: Reset the classifier.
reset() - Method in class moa.classifiers.functions.SPegasos: Reset the classifier.
reset() - Method in class moa.classifiers.meta.LimAttClassifier.CombinationGenerator
reset - Variable in class moa.classifiers.meta.LimAttClassifier
reset() - Method in class moa.classifiers.rules.driftdetection.PageHinkleyFading
reset() - Method in class moa.classifiers.rules.driftdetection.PageHinkleyTest
reset() - Method in class moa.classifiers.rules.functions.Perceptron
reset(double, long) - Method in class moa.classifiers.rules.functions.TargetMean
reset - Variable in class moa.classifiers.rules.RuleClassification
reset - Variable in class moa.classifiers.trees.FIMTDD.FIMTDDPerceptron
reset - Variable in class moa.classifiers.trees.ORTO.ORTOPerceptron
reset() - Method in class moa.core.InputStreamProgressMonitor
reset() - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator
reset(int) - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator
reset() - Method in class moa.evaluation.BasicClusteringPerformanceEvaluator
reset() - Method in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
reset() - Method in class moa.evaluation.BasicRegressionPerformanceEvaluator
reset() - Method in interface moa.evaluation.ClassificationPerformanceEvaluator: Resets this evaluator.
reset() - Method in class moa.evaluation.EWMAClassificationPerformanceEvaluator
reset() - Method in class moa.evaluation.FadingFactorClassificationPerformanceEvaluator
reset() - Method in interface moa.evaluation.LearningPerformanceEvaluator
reset() - Method in class moa.evaluation.MultilabelWindowClassificationPerformanceEvaluator
reset(int) - Method in class moa.evaluation.MultilabelWindowClassificationPerformanceEvaluator
reset() - Method in class moa.evaluation.WindowClassificationPerformanceEvaluator
reset(int) - Method in class moa.evaluation.WindowClassificationPerformanceEvaluator
reset() - Method in class moa.evaluation.WindowRegressionPerformanceEvaluator
reset(int) - Method in class moa.evaluation.WindowRegressionPerformanceEvaluator
reset() - Method in interface moa.recommender.dataset.Dataset
reset() - Method in class moa.recommender.dataset.impl.FlixsterDataset
reset() - Method in class moa.recommender.dataset.impl.JesterDataset
reset() - Method in class moa.recommender.dataset.impl.MovielensDataset
resetButton - Variable in class moa.gui.OptionsConfigurationPanel
resetChange() - Method in class moa.classifiers.core.driftdetection.ADWIN
resetError() - Method in class moa.classifiers.rules.functions.Perceptron
resetError() - Method in class moa.classifiers.rules.functions.TargetMean
resetFF() - Method in class moa.classifiers.trees.ORTO.OptionNode
resetLearning() - Method in class moa.classifiers.AbstractClassifier
resetLearning() - Method in interface moa.classifiers.Classifier: Resets this classifier.
resetLearning() - Method in class moa.classifiers.core.driftdetection.AbstractChangeDetector: Resets this change detector.
resetLearning() - Method in class moa.classifiers.core.driftdetection.ADWINChangeDetector
resetLearning() - Method in interface moa.classifiers.core.driftdetection.ChangeDetector: Resets this change detector.
resetLearning() - Method in class moa.classifiers.core.driftdetection.CusumDM
resetLearning() - Method in class moa.classifiers.core.driftdetection.DDM
resetLearning() - Method in class moa.classifiers.core.driftdetection.EDDM
resetLearning() - Method in class moa.classifiers.core.driftdetection.EnsembleDriftDetectionMethods
resetLearning() - Method in class moa.classifiers.core.driftdetection.EWMAChartDM
resetLearning() - Method in class moa.classifiers.core.driftdetection.GeometricMovingAverageDM
resetLearning() - Method in class moa.classifiers.core.driftdetection.HDDM_A_Test
resetLearning() - Method in class moa.classifiers.core.driftdetection.HDDM_W_Test
resetLearning() - Method in class moa.classifiers.core.driftdetection.PageHinkleyDM
resetLearning() - Method in class moa.classifiers.core.driftdetection.SeqDrift1ChangeDetector
resetLearning() - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector
resetLearning() - Method in class moa.clusterers.AbstractClusterer
resetLearning() - Method in interface moa.clusterers.Clusterer
resetLearning() - Method in class moa.clusterers.outliers.AnyOut.AnyOutCore
resetLearningImpl() - Method in class moa.classifiers.AbstractClassifier: Resets this classifier.
resetLearningImpl() - Method in class moa.classifiers.active.ActiveClassifier
resetLearningImpl() - Method in class moa.classifiers.bayes.NaiveBayes
resetLearningImpl() - Method in class moa.classifiers.bayes.NaiveBayesMultinomial
resetLearningImpl() - Method in class moa.classifiers.drift.DriftDetectionMethodClassifier
resetLearningImpl() - Method in class moa.classifiers.functions.MajorityClass
resetLearningImpl() - Method in class moa.classifiers.functions.NoChange
resetLearningImpl() - Method in class moa.classifiers.functions.Perceptron
resetLearningImpl() - Method in class moa.classifiers.functions.SGD
resetLearningImpl() - Method in class moa.classifiers.functions.SGDMultiClass
resetLearningImpl() - Method in class moa.classifiers.functions.SPegasos
resetLearningImpl() - Method in class moa.classifiers.lazy.kNN
resetLearningImpl() - Method in class moa.classifiers.lazy.kNNwithPAW
resetLearningImpl() - Method in class moa.classifiers.lazy.kNNwithPAWandADWIN
resetLearningImpl() - Method in class moa.classifiers.meta.AccuracyUpdatedEnsemble
resetLearningImpl() - Method in class moa.classifiers.meta.AccuracyWeightedEnsemble
resetLearningImpl() - Method in class moa.classifiers.meta.DACC
resetLearningImpl() - Method in class moa.classifiers.meta.LeveragingBag
resetLearningImpl() - Method in class moa.classifiers.meta.LimAttClassifier
resetLearningImpl() - Method in class moa.classifiers.meta.OCBoost
resetLearningImpl() - Method in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble
resetLearningImpl() - Method in class moa.classifiers.meta.OnlineSmoothBoost
resetLearningImpl() - Method in class moa.classifiers.meta.OzaBag
resetLearningImpl() - Method in class moa.classifiers.meta.OzaBagAdwin
resetLearningImpl() - Method in class moa.classifiers.meta.OzaBagASHT
resetLearningImpl() - Method in class moa.classifiers.meta.OzaBoost
resetLearningImpl() - Method in class moa.classifiers.meta.OzaBoostAdwin
resetLearningImpl() - Method in class moa.classifiers.meta.RandomRules
resetLearningImpl() - Method in class moa.classifiers.meta.TemporallyAugmentedClassifier
resetLearningImpl() - Method in class moa.classifiers.meta.WeightedMajorityAlgorithm
resetLearningImpl() - Method in class moa.classifiers.meta.WEKAClassifier
resetLearningImpl() - Method in class moa.classifiers.multilabel.MajorityLabelset
resetLearningImpl() - Method in class moa.classifiers.multilabel.meta.MLOzaBag
resetLearningImpl() - Method in class moa.classifiers.rules.AbstractAMRules
resetLearningImpl() - Method in class moa.classifiers.rules.AMRulesRegressor: This method initializes and resets the algorithm.
resetLearningImpl() - Method in class moa.classifiers.rules.functions.FadingTargetMean
resetLearningImpl() - Method in class moa.classifiers.rules.functions.Perceptron: A method to reset the model
resetLearningImpl() - Method in class moa.classifiers.rules.functions.TargetMean
resetLearningImpl() - Method in class moa.classifiers.rules.RuleClassifier
resetLearningImpl() - Method in class moa.classifiers.trees.ASHoeffdingTree
resetLearningImpl() - Method in class moa.classifiers.trees.DecisionStump
resetLearningImpl() - Method in class moa.classifiers.trees.FIMTDD
resetLearningImpl() - Method in class moa.classifiers.trees.HoeffdingOptionTree
resetLearningImpl() - Method in class moa.classifiers.trees.HoeffdingTree
resetLearningImpl() - Method in class moa.classifiers.trees.ORTO.ORTOPerceptron: A method to reset the model
resetLearningImpl() - Method in class moa.classifiers.trees.ORTO
resetLearningImpl() - Method in class moa.clusterers.AbstractClusterer
resetLearningImpl() - Method in class moa.clusterers.ClusterGenerator
resetLearningImpl() - Method in class moa.clusterers.clustream.Clustream
resetLearningImpl() - Method in class moa.clusterers.clustream.WithKmeans
resetLearningImpl() - Method in class moa.clusterers.clustree.ClusTree
resetLearningImpl() - Method in class moa.clusterers.CobWeb
resetLearningImpl() - Method in class moa.clusterers.denstream.WithDBSCAN
resetLearningImpl() - Method in class moa.clusterers.outliers.AnyOut.AnyOut
resetLearningImpl() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
resetLearningImpl() - Method in class moa.clusterers.streamkm.StreamKM
resetLearningImpl() - Method in class moa.clusterers.WekaClusteringAlgorithm
resetLearningImpl() - Method in class moa.learners.ChangeDetectorLearner
resetToDefault() - Method in class moa.options.AbstractOption
resetToDefault() - Method in interface moa.options.Option: Resets this option to the default value
resetToDefaults() - Method in class moa.gui.OptionsConfigurationPanel
resetToDefaults() - Method in class moa.options.Options
resetTree - Variable in class moa.classifiers.trees.ASHoeffdingTree
resetTreesOption - Variable in class moa.classifiers.meta.OzaBagASHT
resizeTree(HoeffdingTree.Node, int) - Method in class moa.classifiers.trees.ASHoeffdingTree
restart() - Method in class moa.streams.ArffFileStream
restart() - Method in class moa.streams.CachedInstancesStream
restart() - Method in class moa.streams.clustering.FileStream
restart() - Method in class moa.streams.clustering.RandomRBFGeneratorEvents
restart() - Method in class moa.streams.ConceptDriftRealStream
restart() - Method in class moa.streams.ConceptDriftStream
restart() - Method in class moa.streams.FilteredStream
restart() - Method in class moa.streams.filters.AbstractStreamFilter
restart() - Method in class moa.streams.generators.AgrawalGenerator
restart() - Method in class moa.streams.generators.cd.AbstractConceptDriftGenerator
restart() - Method in class moa.streams.generators.HyperplaneGenerator
restart() - Method in class moa.streams.generators.LEDGenerator
restart() - Method in class moa.streams.generators.multilabel.MetaMultilabelGenerator
restart() - Method in class moa.streams.generators.RandomRBFGenerator
restart() - Method in class moa.streams.generators.RandomTreeGenerator
restart() - Method in class moa.streams.generators.SEAGenerator
restart() - Method in class moa.streams.generators.STAGGERGenerator
restart() - Method in class moa.streams.generators.WaveformGenerator
restart() - Method in interface moa.streams.InstanceStream: Restarts this stream.
restart() - Method in class moa.streams.MultiFilteredStream
restartChangeDetection() - Method in class moa.classifiers.trees.FIMTDD.Node
restartChangeDetection() - Method in class moa.classifiers.trees.FIMTDD.SplitNode
restartImpl() - Method in class moa.streams.filters.AbstractStreamFilter: Restarts this filter.
restartImpl() - Method in class moa.streams.filters.AddNoiseFilter
restartImpl() - Method in class moa.streams.filters.CacheFilter
restartImpl() - Method in class moa.streams.filters.ReplacingMissingValuesFilter
resultingClassDistributionFromSplit(int) - Method in class moa.classifiers.core.AttributeSplitSuggestion
resultingClassDistributions - Variable in class moa.classifiers.core.AttributeSplitSuggestion
resultKnownForInstance(Instance) - Method in class moa.classifiers.core.conditionaltests.InstanceConditionalTest: Gets whether the number of the branch for an instance is known.
resultPreviewer - Variable in class moa.tasks.StandardTaskMonitor
ResultPreviewListener - Interface in moa.tasks: Interface implemented by classes that preview results on the Graphical User Interface
resultPreviewRequested() - Method in class moa.tasks.NullMonitor
resultPreviewRequested - Variable in class moa.tasks.StandardTaskMonitor
resultPreviewRequested() - Method in class moa.tasks.StandardTaskMonitor
resultPreviewRequested() - Method in interface moa.tasks.TaskMonitor: Gets whether there is a request for preview the task result.
resume() - Static method in class moa.gui.visualization.RunOutlierVisualizer
resume() - Static method in class moa.gui.visualization.RunVisualizer
resumeSelectedTasks() - Method in class moa.gui.conceptdrift.CDTaskManagerPanel
resumeSelectedTasks() - Method in class moa.gui.RegressionTaskManagerPanel
resumeSelectedTasks() - Method in class moa.gui.TaskManagerPanel
resumeTask() - Method in class moa.tasks.TaskThread
resumeTaskButton - Variable in class moa.gui.conceptdrift.CDTaskManagerPanel
resumeTaskButton - Variable in class moa.gui.RegressionTaskManagerPanel
resumeTaskButton - Variable in class moa.gui.TaskManagerPanel
revalidate() - Method in class moa.gui.conceptdrift.CDTaskManagerPanel.ProgressCellRenderer
revalidate() - Method in class moa.gui.RegressionTaskManagerPanel.ProgressCellRenderer
revalidate() - Method in class moa.gui.TaskManagerPanel.ProgressCellRenderer
rFactor - Variable in class moa.recommender.rc.predictor.impl.BRISMFPredictor
rFactorOption - Variable in class moa.recommender.predictor.BRISMFPredictor
right - Variable in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserver.Node
right - Variable in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserverRegression.Node
right - Variable in class moa.classifiers.core.attributeclassobservers.FIMTDDNumericAttributeClassObserver.Node
rightStatistics - Variable in class moa.classifiers.core.attributeclassobservers.FIMTDDNumericAttributeClassObserver.Node
Rmc - Variable in class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
rnd - Variable in class moa.recommender.rc.predictor.impl.BRISMFPredictor
root - Variable in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserver
root - Variable in class moa.classifiers.core.attributeclassobservers.FIMTDDNumericAttributeClassObserver
root - Variable in class moa.classifiers.rules.core.attributeclassobservers.FIMTDDNumericAttributeClassLimitObserver.Node
root - Variable in class moa.clusterers.clustree.ClusTree: The root node of the tree.
root - Variable in class moa.clusterers.outliers.utils.mtree.MTree
root1 - Variable in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserverRegression
round(double) - Method in class moa.classifiers.rules.RuleClassifier
round(double) - Method in class moa.gui.TaskTextViewerPanel
rowKappa - Variable in class moa.evaluation.BasicClassificationPerformanceEvaluator
rowKappa - Variable in class moa.evaluation.WindowClassificationPerformanceEvaluator
rp - Variable in class moa.recommender.predictor.BaselinePredictor
rp - Variable in class moa.recommender.predictor.BRISMFPredictor
Rule - Class in moa.classifiers.rules.core
Rule(Rule.Builder) - Constructor for class moa.classifiers.rules.core.Rule
Rule.Builder - Class in moa.classifiers.rules.core
Rule.Builder() - Constructor for class moa.classifiers.rules.core.Rule.Builder
RuleActiveLearningNode - Class in moa.classifiers.rules.core: A modified ActiveLearningNode that uses a Perceptron as the leaf node model, and ensures that the class values sent to the attribute observers are not truncated to ints if regression is being performed
RuleActiveLearningNode(double[]) - Constructor for class moa.classifiers.rules.core.RuleActiveLearningNode: Create a new RuleActiveLearningNode
RuleActiveLearningNode() - Constructor for class moa.classifiers.rules.core.RuleActiveLearningNode
RuleActiveLearningNode(Rule.Builder) - Constructor for class moa.classifiers.rules.core.RuleActiveLearningNode
RuleActiveRegressionNode - Class in moa.classifiers.rules.core: A modified ActiveLearningNode that uses a Perceptron as the leaf node model, and ensures that the class values sent to the attribute observers are not truncated to ints if regression is being performed
RuleActiveRegressionNode(double[]) - Constructor for class moa.classifiers.rules.core.RuleActiveRegressionNode
RuleActiveRegressionNode() - Constructor for class moa.classifiers.rules.core.RuleActiveRegressionNode
RuleActiveRegressionNode(Rule.Builder) - Constructor for class moa.classifiers.rules.core.RuleActiveRegressionNode
ruleAnomaliesIndex - Variable in class moa.classifiers.rules.RuleClassifier
ruleAnomaliesIndexSupervised - Variable in class moa.classifiers.rules.RuleClassifier
ruleAttribAnomalyStatistics - Variable in class moa.classifiers.rules.RuleClassifier
ruleAttribAnomalyStatisticsSupervised - Variable in class moa.classifiers.rules.RuleClassifier
RuleClassification - Class in moa.classifiers.rules
RuleClassification(RuleClassification) - Constructor for class moa.classifiers.rules.RuleClassification
RuleClassification() - Constructor for class moa.classifiers.rules.RuleClassification
RuleClassifier - Class in moa.classifiers.rules: This classifier learn ordered and unordered rule set from data stream.
RuleClassifier() - Constructor for class moa.classifiers.rules.RuleClassifier
RuleClassifierNBayes - Class in moa.classifiers.rules: This classifier learn ordered and unordered rule set from data stream with naive Bayes learners.
RuleClassifierNBayes() - Constructor for class moa.classifiers.rules.RuleClassifierNBayes
ruleClassIndex - Variable in class moa.classifiers.rules.RuleClassifier
ruleEvaluate(Instance) - Method in class moa.classifiers.rules.RuleClassification
ruleNumberID - Variable in class moa.classifiers.rules.AbstractAMRules
ruleNumberID - Variable in class moa.classifiers.rules.core.Rule
ruleSet - Variable in class moa.classifiers.rules.AbstractAMRules
RuleSet - Class in moa.classifiers.rules.core
RuleSet() - Constructor for class moa.classifiers.rules.core.RuleSet
ruleSet - Variable in class moa.classifiers.rules.RuleClassifier
ruleSetAnomalies - Variable in class moa.classifiers.rules.RuleClassifier
ruleSetAnomaliesSupervised - Variable in class moa.classifiers.rules.RuleClassifier
RuleSplitNode - Class in moa.classifiers.rules.nodes: A modified SplitNode method implementing the extra information
RuleSplitNode(InstanceConditionalTest, double[]) - Constructor for class moa.classifiers.rules.nodes.RuleSplitNode: Create a new RuleSplitNode
run() - Method in class moa.gui.BatchCmd
run() - Method in class moa.gui.visualization.RunOutlierVisualizer
run() - Method in class moa.gui.visualization.RunVisualizer
run() - Method in class moa.tasks.TaskThread
runBatch(ClusteringStream, AbstractClusterer, int, int, String) - Static method in class moa.gui.BatchCmd
runningTask - Variable in class moa.tasks.TaskThread
RunOutlierVisualizer - Class in moa.gui.visualization
RunOutlierVisualizer(OutlierVisualTab, OutlierSetupTab) - Constructor for class moa.gui.visualization.RunOutlierVisualizer
RunStreamTasks - Class in moa.tasks: Task for running several experiments modifying values of parameters.
RunStreamTasks() - Constructor for class moa.tasks.RunStreamTasks
runTask(Task) - Method in class moa.gui.conceptdrift.CDTaskManagerPanel
runTask(Task) - Method in class moa.gui.RegressionTaskManagerPanel
runTask(Task) - Method in class moa.gui.TaskManagerPanel
runTaskButton - Variable in class moa.gui.conceptdrift.CDTaskManagerPanel
runTaskButton - Variable in class moa.gui.RegressionTaskManagerPanel
runTaskButton - Variable in class moa.gui.TaskManagerPanel
RunTasks - Class in moa.tasks: Task for running several experiments modifying values of parameters.
RunTasks() - Constructor for class moa.tasks.RunTasks
runVisual() - Method in class moa.gui.visualization.RunVisualizer
RunVisualizer - Class in moa.gui.visualization
RunVisualizer(ClusteringVisualTab, ClusteringSetupTab) - Constructor for class moa.gui.visualization.RunVisualizer

S

sammeOption - Variable in class moa.classifiers.meta.OzaBoostAdwin
sample(Random) - Method in class moa.cluster.Cluster: Samples this cluster by returning a point from inside it.
sample(Random) - Method in class moa.cluster.SphereCluster: Samples this cluster by returning a point from inside it.
sampleFrequencyOption - Variable in class moa.classifiers.meta.WEKAClassifier
sampleFrequencyOption - Variable in class moa.tasks.EvaluateConceptDrift
sampleFrequencyOption - Variable in class moa.tasks.EvaluateInterleavedChunks: Defines how often classifier parameters will be calculated.
sampleFrequencyOption - Variable in class moa.tasks.EvaluateInterleavedTestThenTrain
sampleFrequencyOption - Variable in class moa.tasks.EvaluateOnlineRecommender
sampleFrequencyOption - Variable in class moa.tasks.EvaluatePeriodicHeldOutTest
sampleFrequencyOption - Variable in class moa.tasks.EvaluatePrequential
sampleFrequencyOption - Variable in class moa.tasks.EvaluatePrequentialRegression
saveBestEntropy - Variable in class moa.classifiers.rules.RuleClassifier
saveBestEntropyNominalAttrib - Variable in class moa.classifiers.rules.RuleClassifier
saveBestGlobalEntropy - Variable in class moa.classifiers.rules.RuleClassifier
saveBestValGlobalEntropy - Variable in class moa.classifiers.rules.RuleClassifier
saveLogSelectedTasks() - Method in class moa.gui.conceptdrift.CDTaskManagerPanel
saveLogSelectedTasks() - Method in class moa.gui.RegressionTaskManagerPanel
saveLogSelectedTasks() - Method in class moa.gui.TaskManagerPanel
saveTheBest - Variable in class moa.classifiers.rules.RuleClassifier
scalarProduct(DoubleVector, DoubleVector) - Method in class moa.classifiers.trees.FIMTDD
scaleValues(double) - Method in class moa.core.DoubleVector
scaleXResolution(boolean) - Method in class moa.gui.visualization.GraphCanvas
scaleYResolution(boolean) - Method in class moa.gui.visualization.GraphCanvas
scms - Variable in class moa.classifiers.meta.OzaBoost
scms - Variable in class moa.classifiers.meta.OzaBoostAdwin
screenshot(String, boolean, boolean) - Method in class moa.gui.visualization.StreamOutlierPanel
screenshot(String, boolean, boolean) - Method in class moa.gui.visualization.StreamPanel
scrollPane - Variable in class moa.gui.TaskTextViewerPanel
scrollPane - Variable in class moa.gui.TextViewerPanel
SDRSplitCriterion - Class in moa.classifiers.core.splitcriteria
SDRSplitCriterion() - Constructor for class moa.classifiers.core.splitcriteria.SDRSplitCriterion
SDRSplitCriterionAMRules - Class in moa.classifiers.rules.core.splitcriteria
SDRSplitCriterionAMRules() - Constructor for class moa.classifiers.rules.core.splitcriteria.SDRSplitCriterionAMRules
SEAGenerator - Class in moa.streams.generators: Stream generator for SEA concepts functions.
SEAGenerator() - Constructor for class moa.streams.generators.SEAGenerator
SEAGenerator.ClassFunction - Interface in moa.streams.generators
searchForBestSplitOption(BinaryTreeNumericAttributeClassObserver.Node, AttributeSplitSuggestion, double[], double[], double[], boolean, SplitCriterion, double[], int) - Method in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserver
searchForBestSplitOption(BinaryTreeNumericAttributeClassObserverRegression.Node, AttributeSplitSuggestion, double[], double[], double[], boolean, SplitCriterion, double[], int) - Method in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserverRegression
searchForBestSplitOption(FIMTDDNumericAttributeClassObserver.Node, AttributeSplitSuggestion, SplitCriterion, int) - Method in class moa.classifiers.core.attributeclassobservers.FIMTDDNumericAttributeClassObserver: Implementation of the FindBestSplit algorithm from E.Ikonomovska et al.
second - Variable in class moa.clusterers.outliers.utils.mtree.utils.Pair: The second object.
secondarySplitConfidenceOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree
secondLine - Variable in class moa.gui.TaskTextViewerPanel
secondsToDHMSString(double) - Static method in class moa.core.StringUtils
select(int, int[], int, int, int) - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.MedianOfWidestDimension: Implements computation of the kth-smallest element according to Manber's "Introduction to Algorithms".
SemiSupervisedLearner - Interface in moa.classifiers: Learner interface for incremental semi supervised models.
separatorChar - Variable in class moa.options.ListOption
seqdrift - Variable in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector
seqDrift1 - Variable in class moa.classifiers.core.driftdetection.SeqDrift1ChangeDetector
SeqDrift1ChangeDetector - Class in moa.classifiers.core.driftdetection: SeqDrift1ChangeDetector.java.
SeqDrift1ChangeDetector() - Constructor for class moa.classifiers.core.driftdetection.SeqDrift1ChangeDetector
SeqDrift2ChangeDetector - Class in moa.classifiers.core.driftdetection: SeqDriftChangeDetector.java.
SeqDrift2ChangeDetector() - Constructor for class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector
SeqDrift2ChangeDetector.SeqDrift2 - Class in moa.classifiers.core.driftdetection: SeqDrift2 uses reservoir sampling to build a sequential change detection model that uses statistically sound guarantees defined using Bernstein Bound on false positive and false negative rates.
SeqDrift2ChangeDetector.SeqDrift2(double, int) - Constructor for class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.SeqDrift2: SeqDrift change detector requires two parameters: significance level and block size.
SerializeUtils - Class in moa.core: Class implementing some serialize utility methods.
SerializeUtils() - Constructor for class moa.core.SerializeUtils
SerializeUtils.ByteCountingOutputStream - Class in moa.core
SerializeUtils.ByteCountingOutputStream() - Constructor for class moa.core.SerializeUtils.ByteCountingOutputStream
serialVersionUID - Static variable in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserverRegression
serialVersionUID - Static variable in class moa.classifiers.core.driftdetection.HDDM_W_Test
set(int, T) - Method in class moa.core.AutoExpandVector
set() - Method in class moa.options.FlagOption
set(int, double) - Method in class moa.recommender.rc.utils.DenseVector
set(int, double) - Method in class moa.recommender.rc.utils.SparseVector
set(int, double) - Method in class moa.recommender.rc.utils.Vector
setActiveXDim(int) - Method in class moa.gui.visualization.StreamOutlierPanel
setActiveXDim(int) - Method in class moa.gui.visualization.StreamPanel
setActiveYDim(int) - Method in class moa.gui.visualization.StreamOutlierPanel
setActiveYDim(int) - Method in class moa.gui.visualization.StreamPanel
setAcuity(double) - Method in class moa.clusterers.CobWeb: set the acuity.
setAdaptable(boolean) - Method in class moa.classifiers.trees.ORTO.InnerNode
setAdaptable(boolean) - Method in class moa.classifiers.trees.ORTO.Node
setAlgorithm0ValueAsCLIString(String) - Method in class moa.gui.clustertab.ClusteringAlgoPanel
setAlgorithm0ValueAsCLIString(String) - Method in class moa.gui.outliertab.OutlierAlgoPanel
setAlgorithm1ValueAsCLIString(String) - Method in class moa.gui.clustertab.ClusteringAlgoPanel
setAlgorithm1ValueAsCLIString(String) - Method in class moa.gui.outliertab.OutlierAlgoPanel
setAlternate(boolean) - Method in class moa.classifiers.trees.ORTO.InnerNode
setAlternate(boolean) - Method in class moa.classifiers.trees.ORTO.Node
setAlternateTree(ORTO.Node) - Method in class moa.classifiers.trees.ORTO.InnerNode
setArrayLength(int) - Method in class moa.core.DoubleVector
setAttributeIndices(String) - Method in interface moa.classifiers.lazy.neighboursearch.DistanceFunction: Sets the range of attributes to use in the calculation of the distance.
setAttributeIndices(String) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Sets the range of attributes to use in the calculation of the distance.
setAttributeValue(NumericAttributeBinaryRulePredicate) - Method in class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
setAttributeValue(double) - Method in class moa.classifiers.rules.Predicates
setBestSuggestion(AttributeSplitSuggestion) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
setBuilder(Rule.Builder) - Method in class moa.classifiers.rules.core.Rule
setCenter(double[]) - Method in class moa.cluster.SphereCluster
setChild(int, FIMTDD.Node) - Method in class moa.classifiers.trees.FIMTDD.SplitNode
setChild(int, HoeffdingOptionTree.Node) - Method in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
setChild(int, HoeffdingTree.Node) - Method in class moa.classifiers.trees.HoeffdingTree.SplitNode
setChild(int, ORTO.Node) - Method in class moa.classifiers.trees.ORTO.InnerNode
setChild(int, ORTO.Node) - Method in class moa.classifiers.trees.ORTO.Node
setChild(int, ORTO.Node) - Method in class moa.classifiers.trees.ORTO.SplitNode
setChild(Node) - Method in class moa.clusterers.clustree.Entry: Setter for the child in this entry.
setChosenIndex(int) - Method in class moa.options.MultiChoiceOption
setChosenLabel(String) - Method in class moa.options.MultiChoiceOption
setClassifier(ClassOption) - Method in class weka.classifiers.meta.MOA: Sets the MOA classifier to use.
setClock(int) - Method in class moa.classifiers.core.driftdetection.ADWIN
setClustered() - Method in class moa.clusterers.macro.dbscan.DenseMicroCluster
setClusterEventsList(ArrayList<ClusterEvent>) - Method in class moa.gui.visualization.GraphCanvas
setClusterIDs(Clustering) - Method in class moa.clusterers.macro.AbstractMacroClusterer
setClusteringSetupTab(ClusteringSetupTab) - Method in class moa.gui.clustertab.ClusteringVisualTab
setCurrentActivity(String, double) - Method in class moa.tasks.NullMonitor
setCurrentActivity(String, double) - Method in class moa.tasks.StandardTaskMonitor
setCurrentActivity(String, double) - Method in interface moa.tasks.TaskMonitor: Sets the description and the percentage done of the current activity.
setCurrentActivityDescription(String) - Method in class moa.tasks.NullMonitor
setCurrentActivityDescription(String) - Method in class moa.tasks.StandardTaskMonitor
setCurrentActivityDescription(String) - Method in interface moa.tasks.TaskMonitor: Sets the description of the current activity.
setCurrentActivityFractionComplete(double) - Method in class moa.tasks.NullMonitor
setCurrentActivityFractionComplete(double) - Method in class moa.tasks.StandardTaskMonitor
setCurrentActivityFractionComplete(double) - Method in interface moa.tasks.TaskMonitor: Sets the percentage done of the current activity
setCurrentObject(Object) - Method in class moa.options.AbstractClassOption: Sets current object.
setCutoff(double) - Method in class moa.clusterers.CobWeb: set the cutoff
setDimensionComobBoxes(int) - Method in class moa.gui.clustertab.ClusteringVisualTab
setDimensionComobBoxes(int) - Method in class moa.gui.outliertab.OutlierVisualTab
setDirection(double[]) - Method in class moa.gui.visualization.ClusterPanel
setDirection(double[]) - Method in class moa.gui.visualization.OutlierPanel
setDistanceFunction(DistanceFunction) - Method in class moa.classifiers.lazy.neighboursearch.KDTree: sets the distance function to use for nearest neighbour search.
setDistanceFunction(DistanceFunction) - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch: sets the distance function to use for nearest neighbour search.
setDontNormalize(boolean) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Sets whether if the attribute values are to be normalized in distance calculation.
setEditState(String) - Method in class moa.gui.ClassOptionEditComponent
setEditState(String) - Method in class moa.gui.ClassOptionWithNamesEditComponent
setEditState(String) - Method in class moa.gui.FileOptionEditComponent
setEditState(String) - Method in class moa.gui.FlagOptionEditComponent
setEditState(String) - Method in class moa.gui.FloatOptionEditComponent
setEditState(String) - Method in class moa.gui.IntOptionEditComponent
setEditState(String) - Method in class moa.gui.MultiChoiceOptionEditComponent
setEditState(String) - Method in interface moa.gui.OptionEditComponent: Sets the state of the component
setEditState(String) - Method in class moa.gui.StringOptionEditComponent
setEditState(String) - Method in class moa.gui.WEKAClassOptionEditComponent
setEnabled(int, boolean) - Method in class moa.evaluation.MeasureCollection
setEuclideanDistanceFunction(EuclideanDistance) - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter: Sets the EuclideanDistance object to use for splitting nodes.
setEvents - Variable in class moa.clusterers.outliers.MCOD.MCODBase.EventQueue
setEvents - Variable in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase.EventQueue
setEventsList(ArrayList<ClusterEvent>) - Method in class moa.tasks.ConceptDriftMainTask
setEventsList(ArrayList<ClusterEvent>) - Method in class moa.tasks.RegressionMainTask
setExamplesSeenAtLastSplitEvaluation(double) - Method in class moa.classifiers.trees.FIMTDD.LeafNode
setFirst(T) - Method in class moa.recommender.rc.utils.Pair
setGenerator(ClassOption) - Method in class weka.datagenerators.classifiers.classification.MOA: Sets the MOA stream generator to use.
setGraph(String) - Method in class moa.gui.TaskTextViewerPanel
setGraph(MeasureCollection, MeasureCollection, int, int) - Method in class moa.gui.visualization.GraphCanvas
setGraph(MeasureCollection, MeasureCollection, int) - Method in class moa.gui.visualization.GraphCurve
setGroundTruth(double) - Method in class moa.cluster.Cluster
setGroundTruthLayerVisibility(boolean) - Method in class moa.gui.visualization.StreamPanel
setGroundTruthVisibility(boolean) - Method in class moa.gui.visualization.RunVisualizer
setHighlightedClusterPanel(ClusterPanel) - Method in class moa.gui.visualization.StreamPanel
setHighlightedOutlierPanel(OutlierPanel) - Method in class moa.gui.visualization.StreamOutlierPanel
setId(double) - Method in class moa.cluster.Cluster
setId(int) - Method in class moa.clusterers.outliers.AnyOut.util.DataObject
setInput(double) - Method in class moa.classifiers.core.driftdetection.ADWIN
setInput(double, double) - Method in class moa.classifiers.core.driftdetection.ADWIN
setInput(double) - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.SeqDrift2: This method can be used to directly interface with SeqDrift change detector.
setInputStream(InstanceStream) - Method in class moa.streams.filters.AbstractStreamFilter
setInputStream(InstanceStream) - Method in interface moa.streams.filters.StreamFilter: Sets the input stream to the filter
setInstanceList(int[]) - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter: Sets the master index array containing indices of the training instances.
setInstances(Instances) - Method in interface moa.classifiers.lazy.neighboursearch.DistanceFunction: Sets the instances.
setInstances(Instances) - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Builds the KDTree on the given set of instances.
setInstances(Instances) - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter: Sets the training instances on which the tree is (or is to be) built.
setInstances(Instances) - Method in class moa.classifiers.lazy.neighboursearch.LinearNNSearch: Sets the instances comprising the current neighbourhood.
setInstances(Instances) - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch: Sets the instances.
setInstances(Instances) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Sets the instances.
setInstancesSeen(int) - Method in class moa.classifiers.rules.functions.Perceptron
setInvertSelection(boolean) - Method in interface moa.classifiers.lazy.neighboursearch.DistanceFunction: Sets whether the matching sense of attribute indices is inverted or not.
setInvertSelection(boolean) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Sets whether the matching sense of attribute indices is inverted or not.
setLambda(double) - Method in class moa.classifiers.functions.SGD: Set the value of lambda to use
setLambda(double) - Method in class moa.classifiers.functions.SGDMultiClass: Set the value of lambda to use
setLambda(double) - Method in class moa.classifiers.functions.SPegasos: Set the value of lambda to use
setLatestPreview(Object) - Method in class moa.gui.PreviewPanel
setLatestResultPreview(Object) - Method in class moa.tasks.NullMonitor
setLatestResultPreview(Object) - Method in class moa.tasks.StandardTaskMonitor
setLatestResultPreview(Object) - Method in interface moa.tasks.TaskMonitor: Sets the current result to preview
setLearningNode(RuleActiveLearningNode) - Method in class moa.classifiers.rules.core.Rule
setLearningRate(double) - Method in class moa.classifiers.functions.SGD: Set the learning rate.
setLearningRate(double) - Method in class moa.classifiers.functions.SGDMultiClass: Set the learning rate.
setLearningRatio(double) - Method in class moa.classifiers.rules.functions.Perceptron
setList(Option[]) - Method in class moa.options.ListOption
setlistAttributes(int[]) - Method in class moa.classifiers.trees.LimAttHoeffdingTree.LimAttLearningNode
setlistAttributes(int[]) - Method in class moa.classifiers.trees.LimAttHoeffdingTree
setLossFunction(int) - Method in class moa.classifiers.functions.SGD: Set the loss function to use.
setLossFunction(int) - Method in class moa.classifiers.functions.SGDMultiClass: Set the loss function to use.
setLossFunction(int) - Method in class moa.classifiers.functions.SPegasos: Set the loss function to use.
setLRate(double) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
setMacroLayerVisibility(boolean) - Method in class moa.gui.visualization.StreamPanel
setMacroVisibility(boolean) - Method in class moa.gui.visualization.RunVisualizer
setMaxInstInLeaf(int) - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Sets the maximum number of instances in a leaf.
setMaxSize(int) - Method in class moa.classifiers.trees.ASHoeffdingTree
setMaxXValue(int) - Method in class moa.gui.visualization.GraphAxes
setMC - Variable in class moa.clusterers.outliers.MCOD.MCODBase
setMeasurePerformance(boolean) - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Sets whether to calculate the performance statistics or not.
setMeasures(MeasureCollection[], MeasureCollection[], ActionListener) - Method in class moa.gui.clustertab.ClusteringVisualEvalPanel
setMeasures(MeasureCollection[], ActionListener) - Method in class moa.gui.outliertab.OutlierVisualEvalPanel
setMeasureValue(String, String) - Method in class moa.cluster.Cluster
setMeasureValue(String, double) - Method in class moa.cluster.Cluster
setMeasureValue(String, double) - Method in class moa.gui.visualization.DataPoint
setMeasureValue(String, String) - Method in class moa.gui.visualization.DataPoint
SetMessagePrinter(MyBaseOutlierDetector.PrintMsg) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
setMicroLayerVisibility(boolean) - Method in class moa.gui.visualization.RunVisualizer
setMicroLayerVisibility(boolean) - Method in class moa.gui.visualization.StreamPanel
setMinBoxRelWidth(double) - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Sets the minimum relative box width.
setModelContext(InstancesHeader) - Method in class moa.classifiers.AbstractClassifier
setModelContext(InstancesHeader) - Method in interface moa.classifiers.Classifier: Sets the reference to the header of the data stream.
setModelContext(InstancesHeader) - Method in class moa.classifiers.lazy.kNN
setModelContext(InstancesHeader) - Method in class moa.classifiers.multilabel.MajorityLabelset
setModelContext(InstancesHeader) - Method in class moa.classifiers.multilabel.MEKAClassifier
setModelContext(InstancesHeader) - Method in class moa.classifiers.multilabel.meta.MLOzaBag
setModelContext(InstancesHeader) - Method in class moa.classifiers.multilabel.meta.MLOzaBagAdwin
setModelContext(InstancesHeader) - Method in class moa.classifiers.multilabel.MultilabelHoeffdingTree
setModelContext(InstancesHeader) - Method in class moa.clusterers.AbstractClusterer
setModelContext(InstancesHeader) - Method in interface moa.clusterers.Clusterer
setN(double) - Method in class moa.cluster.CFCluster
setNIterations(int) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
setNode(Node) - Method in class moa.clusterers.clustree.Entry
setNodeList(List<RuleSplitNode>) - Method in class moa.classifiers.rules.core.Rule
setNodeSplitter(KDTreeNodeSplitter) - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Sets the splitting method to use to split the nodes of the KDTree.
setNodeWidthNormalization(boolean) - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter: Sets whether if a nodes region is normalized or not.
setNormalizeNodeWidth(boolean) - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Sets the flag for normalizing the widths of a KDTree Node by the width of the dimension in the universe.
setNumLabels(int) - Method in class moa.core.MultilabelInstance
setOptions(String[]) - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.MOA: Parses a given list of options.
setOptions(String[]) - Method in class weka.datagenerators.classifiers.classification.MOA: Parses a list of options for this object.
setOutiler(boolean) - Method in class moa.clusterers.outliers.AnyOut.util.DataObject
setOutlierDetector(MyBaseOutlierDetector) - Method in class moa.gui.visualization.StreamOutlierPanel
setOutlierSetupTab(OutlierSetupTab) - Method in class moa.gui.outliertab.OutlierVisualTab
setOutliersVisibility(boolean) - Method in class moa.gui.visualization.RunOutlierVisualizer
setOutliersVisibility(boolean) - Method in class moa.gui.visualization.StreamOutlierPanel
setOwner(Rule) - Method in class moa.classifiers.rules.core.Rule.Builder
setPanelTitle(String) - Method in class moa.gui.clustertab.ClusteringAlgoPanel
setPanelTitle(String) - Method in class moa.gui.outliertab.OutlierAlgoPanel
setParent(FIMTDD.SplitNode) - Method in class moa.classifiers.trees.FIMTDD.Node: Set the parent node
setParent(ORTO.InnerNode) - Method in class moa.classifiers.trees.ORTO.Node: Set the parent node
setParentEntry(Entry) - Method in class moa.clusterers.clustree.Entry
setPauseInterval(int) - Method in class moa.gui.clustertab.ClusteringVisualTab
setPauseInterval(int) - Method in class moa.gui.outliertab.OutlierVisualTab
setPerceptron(Perceptron) - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
setPointLayerVisibility(boolean) - Method in class moa.gui.visualization.RunVisualizer
setPointsVisibility(boolean) - Method in class moa.gui.visualization.RunOutlierVisualizer
setPointsVisibility(boolean) - Method in class moa.gui.visualization.StreamOutlierPanel
setPointVisibility(boolean) - Method in class moa.gui.visualization.StreamPanel
setPreviewPanel(PreviewPanel) - Method in class moa.gui.conceptdrift.CDTaskManagerPanel
setPreviewPanel(PreviewPanel) - Method in class moa.gui.RegressionTaskManagerPanel
setPreviewPanel(PreviewPanel) - Method in class moa.gui.TaskManagerPanel
setProcessedPointsCounter(int) - Method in class moa.gui.clustertab.ClusteringVisualTab
setProcessedPointsCounter(int) - Method in class moa.gui.outliertab.OutlierVisualTab
setProcessFrequency(int) - Method in class moa.gui.visualization.GraphAxes
SetProgressInterval(int) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
setRadius(double) - Method in class moa.cluster.SphereCluster
setRandomSeed(int) - Method in class moa.classifiers.AbstractClassifier
setRandomSeed(int) - Method in interface moa.classifiers.Classifier: Sets the seed for random number generation.
setRandomSeed(int) - Method in class moa.clusterers.AbstractClusterer
setRandomSeed(int) - Method in interface moa.clusterers.Clusterer
setRating(int, int, double) - Method in class moa.recommender.rc.data.AbstractRecommenderData
setRating(int, int, double) - Method in class moa.recommender.rc.data.impl.MemRecommenderData
setRating(int, int, double) - Method in interface moa.recommender.rc.data.RecommenderData
setResetTree() - Method in class moa.classifiers.trees.ASHoeffdingTree
setRFactor(double) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
setRuleNumberID(int) - Method in class moa.classifiers.rules.core.Rule
setSaveInstanceData(boolean) - Method in class moa.clusterers.CobWeb: Set the value of saveInstances.
setSecond(U) - Method in class moa.recommender.rc.utils.Pair
setSeed(long) - Method in class moa.clusterers.streamkm.MTRandom: This method resets the state of this instance using the 64 bits of seed data provided.
setSeed(byte[]) - Method in class moa.clusterers.streamkm.MTRandom: This method resets the state of this instance using the byte array of seed data provided.
setSeed(int[]) - Method in class moa.clusterers.streamkm.MTRandom: This method resets the state of this instance using the integer array of seed data provided.
SetShowProgress(boolean) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
setSkipIdentical(boolean) - Method in class moa.classifiers.lazy.neighboursearch.LinearNNSearch: Sets the property to skip identical instances (with distance zero from the target) from the set of neighbours returned.
setSourceClustering(Clustering) - Method in class moa.clusterers.ClusterGenerator
setSpeed(int) - Method in class moa.gui.visualization.RunOutlierVisualizer
setSpeed(int) - Method in class moa.gui.visualization.RunVisualizer
setSplitIndex(int) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
setStatisticsBranchSplit(double[]) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
setStatisticsNewRuleActiveLearningNode(double[]) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
setStatisticsOtherBranchSplit(double[]) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
setStreamValueAsCLIString(String) - Method in class moa.gui.clustertab.ClusteringAlgoPanel
setStreamValueAsCLIString(String) - Method in class moa.gui.outliertab.OutlierAlgoPanel
setSymbol(double) - Method in class moa.classifiers.rules.Predicates
setTargetMean(TargetMean) - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
setTaskString(String) - Method in class moa.gui.conceptdrift.CDTaskManagerPanel
setTaskString(String, boolean) - Method in class moa.gui.conceptdrift.CDTaskManagerPanel
setTaskString(String) - Method in class moa.gui.RegressionTaskManagerPanel
setTaskString(String, boolean) - Method in class moa.gui.RegressionTaskManagerPanel
setTaskString(String) - Method in class moa.gui.TaskManagerPanel
setTaskString(String, boolean) - Method in class moa.gui.TaskManagerPanel
setTaskThreadToPreview(TaskThread) - Method in class moa.gui.PreviewPanel
setText(String) - Method in class moa.gui.TaskTextViewerPanel
setText(String) - Method in class moa.gui.TextViewerPanel
setTimestamp(long) - Method in class moa.clusterers.denstream.Timestamp
SetTrace(boolean) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
SetUserInfo(boolean, boolean, MyBaseOutlierDetector.PrintMsg, int) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
setValue(double) - Method in class moa.classifiers.rules.Predicates
setValue(int, double) - Method in class moa.core.DoubleVector
setValue(boolean) - Method in class moa.options.FlagOption
setValue(double) - Method in class moa.options.FloatOption
setValue(int) - Method in class moa.options.IntOption
setValue(String) - Method in class moa.options.StringOption
setValueViaCLIString(String) - Method in class moa.options.AbstractClassOption
setValueViaCLIString(String) - Method in class moa.options.ClassOption
setValueViaCLIString(String) - Method in class moa.options.ClassOptionWithNames
setValueViaCLIString(String) - Method in class moa.options.FlagOption
setValueViaCLIString(String) - Method in class moa.options.FloatOption
setValueViaCLIString(String) - Method in class moa.options.IntOption
setValueViaCLIString(String) - Method in class moa.options.ListOption
setValueViaCLIString(String) - Method in class moa.options.MultiChoiceOption
setValueViaCLIString(String) - Method in interface moa.options.Option: Sets value of this option via the Command Line Interface text
setValueViaCLIString(String) - Method in class moa.options.StringOption
setValueViaCLIString(String) - Method in class moa.options.WEKAClassOption
setViaCLIString(String) - Method in class moa.options.Options
setViewport(JViewport) - Method in class moa.gui.visualization.GraphCanvas
setVisited() - Method in class moa.clusterers.macro.dbscan.DenseMicroCluster
setVisualizer(RunOutlierVisualizer) - Method in class moa.gui.visualization.StreamOutlierPanel
setW(int) - Method in class moa.classifiers.core.driftdetection.ADWIN
setWaitWinFull(boolean) - Method in class moa.gui.visualization.RunOutlierVisualizer
setWeight(double) - Method in class moa.cluster.SphereCluster
setWeights(double[][]) - Method in class moa.classifiers.functions.Perceptron
setWeights(double[]) - Method in class moa.classifiers.rules.functions.Perceptron
setWeights(double[]) - Method in class moa.classifiers.trees.ORTO.ORTOPerceptron
setWeightSeenAtLastSplitEvaluation(double) - Method in class moa.classifiers.trees.HoeffdingOptionTree.ActiveLearningNode
setWeightSeenAtLastSplitEvaluation(double) - Method in class moa.classifiers.trees.HoeffdingTree.ActiveLearningNode
setXMaxValue(int) - Method in class moa.gui.visualization.GraphAxes
setXResolution(double) - Method in class moa.gui.visualization.GraphAxes
setYMinMaxValues(double, double) - Method in class moa.gui.visualization.GraphAxes
setYMinMaxValues(double, double) - Method in class moa.gui.visualization.GraphCurve
setZoom(int, int, int, JScrollPane) - Method in class moa.gui.visualization.StreamOutlierPanel
setZoom(int, int, int, JScrollPane) - Method in class moa.gui.visualization.StreamPanel
SGD - Class in moa.classifiers.functions: Implements stochastic gradient descent for learning various linear models (binary class SVM, binary class logistic regression and linear regression).
SGD() - Constructor for class moa.classifiers.functions.SGD
SGDMultiClass - Class in moa.classifiers.functions: Implements stochastic gradient descent for learning various linear models (binary class SVM, binary class logistic regression and linear regression).
SGDMultiClass() - Constructor for class moa.classifiers.functions.SGDMultiClass
shallowClear() - Method in class moa.clusterers.clustree.Entry: Clear the data and the buffer Custer in this entry.
showEditOptionsDialog(Component, String, OptionHandler) - Static method in class moa.gui.OptionsConfigurationPanel
showErrorDialog(Component, String, String) - Static method in class moa.gui.GUIUtils
showExceptionDialog(Component, String, Exception) - Static method in class moa.gui.GUIUtils
showHelpDialog() - Method in class moa.gui.OptionsConfigurationPanel
ShowProgress(String) - Method in interface moa.clusterers.outliers.MyBaseOutlierDetector.ProgressInfo
ShowProgress(String) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
ShowProgress(String, boolean) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
showSelectClassDialog(Component, String, Class<?>, String, String) - Static method in class moa.gui.ClassOptionSelectionPanel
showSelectClassDialog(Component, String, Class<?>, String, String, String[]) - Static method in class moa.gui.ClassOptionWithNamesSelectionPanel
shuffleRandomSeedOption - Variable in class moa.tasks.CacheShuffledStream
sigma - Variable in class moa.streams.generators.HyperplaneGenerator
sigmaPercentageOption - Variable in class moa.streams.generators.HyperplaneGenerator
SilhouetteCoefficient - Class in moa.evaluation
SilhouetteCoefficient() - Constructor for class moa.evaluation.SilhouetteCoefficient
SimpleBudget - Class in moa.clusterers.clustree.util
SimpleBudget(int) - Constructor for class moa.clusterers.clustree.util.SimpleBudget
SimpleCOD - Class in moa.clusterers.outliers.SimpleCOD
SimpleCOD() - Constructor for class moa.clusterers.outliers.SimpleCOD.SimpleCOD
SimpleCODBase - Class in moa.clusterers.outliers.SimpleCOD
SimpleCODBase() - Constructor for class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
SimpleCODBase.EventItem - Class in moa.clusterers.outliers.SimpleCOD
SimpleCODBase.EventItem(ISBIndex.ISBNode, Long) - Constructor for class moa.clusterers.outliers.SimpleCOD.SimpleCODBase.EventItem
SimpleCODBase.EventQueue - Class in moa.clusterers.outliers.SimpleCOD
SimpleCODBase.EventQueue() - Constructor for class moa.clusterers.outliers.SimpleCOD.SimpleCODBase.EventQueue
SingleClassifierDrift - Class in moa.classifiers.drift: Class for handling concept drift datasets with a wrapper on a classifier.
SingleClassifierDrift() - Constructor for class moa.classifiers.drift.SingleClassifierDrift
size() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.MyHeap: returns the size of the heap.
size() - Method in class moa.cluster.Clustering
size() - Method in class moa.clusterers.outliers.AnyOut.util.DataSet: Returns the size of the set.
size() - Method in class moa.recommender.rc.utils.DenseVector
size() - Method in class moa.recommender.rc.utils.SparseVector
size() - Method in class moa.recommender.rc.utils.Vector
sizeCoresetOption - Variable in class moa.clusterers.streamkm.StreamKM
SizeOf - Class in moa.core: Helper class for Maxim Zakharenkov's SizeOf agent.
SizeOf() - Constructor for class moa.core.SizeOf
sizeOf(Object) - Static method in class moa.core.SizeOf: Returns the size of the object.
SizeWindow - Variable in class moa.evaluation.WindowClassificationPerformanceEvaluator.Estimator
SizeWindow - Variable in class moa.evaluation.WindowRegressionPerformanceEvaluator.Estimator
skewOption - Variable in class moa.streams.generators.multilabel.MetaMultilabelGenerator
skip(long) - Method in class moa.core.InputStreamProgressMonitor
skipIdenticalTipText() - Method in class moa.classifiers.lazy.neighboursearch.LinearNNSearch: Returns the tip text for this property.
slider - Variable in class moa.gui.FloatOptionEditComponent
slider - Variable in class moa.gui.IntOptionEditComponent
SLIDER_RESOLUTION - Static variable in class moa.gui.FloatOptionEditComponent
sliderValueToFloatValue(int) - Method in class moa.gui.FloatOptionEditComponent
SlidingMidPointOfWidestSide - Class in moa.classifiers.lazy.neighboursearch.kdtrees: The class that splits a node into two based on the midpoint value of the dimension in which the node's rectangle is widest.
SlidingMidPointOfWidestSide() - Constructor for class moa.classifiers.lazy.neighboursearch.kdtrees.SlidingMidPointOfWidestSide
smoothingOption - Variable in class moa.classifiers.meta.OCBoost
smoothOption - Variable in class moa.tasks.Plot: Determines whether to smooth the plot with bezier curves.
sortByValue(Map<K, V>) - Static method in class moa.streams.filters.ReplacingMissingValuesFilter.MapUtil
sp - Variable in class moa.gui.visualization.PointPanel
SparseVector - Class in moa.recommender.rc.utils
SparseVector() - Constructor for class moa.recommender.rc.utils.SparseVector
SparseVector(Map<Integer, Double>) - Constructor for class moa.recommender.rc.utils.SparseVector
SparseVector.SparseVectorIterator - Class in moa.recommender.rc.utils
SparseVector.SparseVectorIterator() - Constructor for class moa.recommender.rc.utils.SparseVector.SparseVectorIterator
speedCentroids - Variable in class moa.streams.generators.RandomRBFGeneratorDrift
speedChangeOption - Variable in class moa.streams.generators.RandomRBFGeneratorDrift
speedOption - Variable in class moa.clusterers.denstream.WithDBSCAN
speedOption - Variable in class moa.streams.clustering.RandomRBFGeneratorEvents
speedRangeOption - Variable in class moa.streams.clustering.RandomRBFGeneratorEvents
SPegasos - Class in moa.classifiers.functions: Implements the stochastic variant of the Pegasos (Primal Estimated sub-GrAdient SOlver for SVM) method of Shalev-Shwartz et al.
SPegasos() - Constructor for class moa.classifiers.functions.SPegasos
SphereCluster - Class in moa.cluster: A simple implementation of the Cluster interface representing spherical clusters.
SphereCluster(double[], double) - Constructor for class moa.cluster.SphereCluster
SphereCluster() - Constructor for class moa.cluster.SphereCluster
SphereCluster(double[], double, double) - Constructor for class moa.cluster.SphereCluster
SphereCluster(int, double, Random) - Constructor for class moa.cluster.SphereCluster
SphereCluster(List<? extends Instance>, int) - Constructor for class moa.cluster.SphereCluster
spinner - Variable in class moa.gui.FloatOptionEditComponent
spinner - Variable in class moa.gui.IntOptionEditComponent
split() - Method in class moa.classifiers.rules.core.Rule
splitAttIndex - Variable in class moa.streams.generators.RandomTreeGenerator.Node
splitAttValue - Variable in class moa.streams.generators.RandomTreeGenerator.Node
splitConfidenceOption - Variable in class moa.classifiers.rules.AbstractAMRules
splitConfidenceOption - Variable in class moa.classifiers.rules.RuleClassifier
splitConfidenceOption - Variable in class moa.classifiers.trees.FIMTDD
splitConfidenceOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree
splitConfidenceOption - Variable in class moa.classifiers.trees.HoeffdingTree
splitConfidenceOption - Variable in class moa.classifiers.trees.ORTO
SplitCriterion - Interface in moa.classifiers.core.splitcriteria: Interface for computing splitting criteria.
splitCriterionOption - Variable in class moa.classifiers.trees.DecisionStump
splitCriterionOption - Variable in class moa.classifiers.trees.FIMTDD
splitCriterionOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree
splitCriterionOption - Variable in class moa.classifiers.trees.HoeffdingTree
splitCriterionOption - Variable in class moa.classifiers.trees.ORTO
splitFunction - Variable in class moa.clusterers.outliers.utils.mtree.MTree
SplitFunction<DATA> - Interface in moa.clusterers.outliers.utils.mtree: Defines an object to be used to split a node in an M-Tree.
SplitFunction.SplitResult<DATA> - Class in moa.clusterers.outliers.utils.mtree: An object used as the result for the SplitFunction.process(Set, DistanceFunction) method.
SplitFunction.SplitResult(Pair<DATA>, Pair<Set<DATA>>) - Constructor for class moa.clusterers.outliers.utils.mtree.SplitFunction.SplitResult: The constructor for a SplitFunction.SplitResult object.
splitIndex - Variable in class moa.classifiers.rules.core.RuleActiveLearningNode
splitNode(KDTreeNode, int, double[][], double[][]) - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter: Splits a node into two.
splitNode(KDTreeNode, int, double[][], double[][]) - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KMeansInpiredMethod: Splits a node into two such that the overall sum of squared distances of points to their centres on both sides of the (axis-parallel) splitting plane is minimum.
splitNode(KDTreeNode, int, double[][], double[][]) - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.MedianOfWidestDimension: Splits a node into two based on the median value of the dimension in which the points have the widest spread.
splitNode(KDTreeNode, int, double[][], double[][]) - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.MidPointOfWidestDimension: Splits a node into two based on the midpoint value of the dimension in which the points have the widest spread.
splitNode(KDTreeNode, int, double[][], double[][]) - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.SlidingMidPointOfWidestSide: Splits a node into two based on the midpoint value of the dimension in which the node's rectangle is widest.
splitNodes(KDTreeNode, double[][], int) - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Recursively splits nodes of a tree starting from the supplied node.
splitParameterFromRemainingOptions(String) - Static method in class moa.options.Options: Internal method that splits a string into two parts - the parameter for the current option, and the remaining options.
splitRatioStatistics - Variable in class moa.classifiers.trees.ORTO.ActiveLearningNode
splitTest - Variable in class moa.classifiers.core.AttributeSplitSuggestion
splitTest - Variable in class moa.classifiers.trees.FIMTDD.SplitNode
splitTest - Variable in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
splitTest - Variable in class moa.classifiers.trees.HoeffdingTree.SplitNode
splitTest - Variable in class moa.classifiers.trees.ORTO.SplitNode
sqDifference(int, double, double) - Method in class moa.classifiers.lazy.neighboursearch.EuclideanDistance: Returns the squared difference of two values of an attribute.
squared_radius() - Method in class moa.cluster.Miniball: Return the sqaured Radius of the miniball
squaredActualClassStatistics - Variable in class moa.classifiers.rules.RuleClassification
squaredAttributeStatistics - Variable in class moa.classifiers.rules.RuleClassification
squaredAttributeStatistics - Variable in class moa.classifiers.trees.ORTO.ORTOPerceptron
squaredAttributeStatisticsSupervised - Variable in class moa.classifiers.rules.RuleClassification
SQUAREDLOSS - Static variable in class moa.classifiers.functions.SGD
SQUAREDLOSS - Static variable in class moa.classifiers.functions.SGDMultiClass
squaredperceptronattributeStatistics - Variable in class moa.classifiers.rules.functions.Perceptron
squaredperceptronsumY - Variable in class moa.classifiers.rules.functions.Perceptron
squareError - Variable in class moa.evaluation.BasicRegressionPerformanceEvaluator
squareError - Variable in class moa.evaluation.WindowRegressionPerformanceEvaluator
squareTargetError - Variable in class moa.evaluation.BasicRegressionPerformanceEvaluator
SS - Variable in class moa.cluster.CFCluster: Squared sum of all the points added to the cluster.
SSQ - Class in moa.evaluation
SSQ() - Constructor for class moa.evaluation.SSQ
SST - Variable in class moa.clusterers.clustream.ClustreamKernel
stabIndexSizeOption - Variable in class moa.classifiers.meta.ADACC: Threshold for the stability index
STAGGERGenerator - Class in moa.streams.generators: Stream generator for STAGGER Concept functions.
STAGGERGenerator() - Constructor for class moa.streams.generators.STAGGERGenerator
STAGGERGenerator.ClassFunction - Interface in moa.streams.generators
StandardTaskMonitor - Class in moa.tasks: Class that represents a standard task monitor.
StandardTaskMonitor() - Constructor for class moa.tasks.StandardTaskMonitor
StatisticalCollection - Class in moa.evaluation
StatisticalCollection() - Constructor for class moa.evaluation.StatisticalCollection
statistics - Variable in class moa.classifiers.rules.AbstractAMRules
statistics - Variable in class moa.classifiers.rules.core.Rule.Builder
statistics(double[]) - Method in class moa.classifiers.rules.core.Rule.Builder
statisticsBranchSplit - Variable in class moa.classifiers.rules.core.RuleActiveLearningNode
statisticsNewRuleActiveLearningNode - Variable in class moa.classifiers.rules.core.RuleActiveLearningNode
statisticsOtherBranchSplit() - Method in class moa.classifiers.rules.core.Rule
statisticsOtherBranchSplit - Variable in class moa.classifiers.rules.core.RuleActiveLearningNode
stdDev - Variable in class moa.streams.generators.RandomRBFGenerator.Centroid
stepOption - Variable in class moa.classifiers.active.ActiveClassifier
stop() - Method in class moa.gui.visualization.RunOutlierVisualizer
stop() - Method in class moa.gui.visualization.RunVisualizer
stopMemManagementOption - Variable in class moa.classifiers.trees.HoeffdingTree
stopRun() - Method in class moa.gui.clustertab.ClusteringSetupTab
stopRun() - Method in class moa.gui.outliertab.OutlierSetupTab
stopVisualizer() - Method in class moa.gui.clustertab.ClusteringVisualTab
stopVisualizer() - Method in class moa.gui.outliertab.OutlierVisualTab
storedCountOption - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble: Number of classifiers remembered and available for ensemble construction.
storedLearners - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble
storedWeights - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble: The weights of stored classifiers.
STORMBase - Class in moa.clusterers.outliers.Angiulli
STORMBase() - Constructor for class moa.clusterers.outliers.Angiulli.STORMBase
StreamFilter - Interface in moa.streams.filters: Interface representing a stream filter.
streamHeader - Variable in class moa.streams.clustering.RandomRBFGeneratorEvents
streamHeader - Variable in class moa.streams.ConceptDriftRealStream
streamHeader - Variable in class moa.streams.generators.AgrawalGenerator
streamHeader - Variable in class moa.streams.generators.cd.AbstractConceptDriftGenerator
streamHeader - Variable in class moa.streams.generators.HyperplaneGenerator
streamHeader - Variable in class moa.streams.generators.LEDGenerator
streamHeader - Variable in class moa.streams.generators.RandomRBFGenerator
streamHeader - Variable in class moa.streams.generators.RandomTreeGenerator
streamHeader - Variable in class moa.streams.generators.SEAGenerator
streamHeader - Variable in class moa.streams.generators.STAGGERGenerator
streamHeader - Variable in class moa.streams.generators.WaveformGenerator
StreamKM - Class in moa.clusterers.streamkm
StreamKM() - Constructor for class moa.clusterers.streamkm.StreamKM
StreamObj - Class in moa.clusterers.outliers.AbstractC
StreamObj(double...) - Constructor for class moa.clusterers.outliers.AbstractC.StreamObj
StreamObj - Class in moa.clusterers.outliers.Angiulli
StreamObj(double...) - Constructor for class moa.clusterers.outliers.Angiulli.StreamObj
StreamObj - Class in moa.clusterers.outliers.MCOD
StreamObj(double...) - Constructor for class moa.clusterers.outliers.MCOD.StreamObj
StreamObj - Class in moa.clusterers.outliers.SimpleCOD
StreamObj(double...) - Constructor for class moa.clusterers.outliers.SimpleCOD.StreamObj
streamOption - Variable in class moa.streams.ConceptDriftRealStream
streamOption - Variable in class moa.streams.ConceptDriftStream
streamOption - Variable in class moa.streams.FilteredStream
streamOption - Variable in class moa.streams.MultiFilteredStream
streamOption - Variable in class moa.tasks.CacheShuffledStream
streamOption - Variable in class moa.tasks.EvaluateClustering
streamOption - Variable in class moa.tasks.EvaluateConceptDrift
streamOption - Variable in class moa.tasks.EvaluateInterleavedChunks: Allows to select the stream the classifier will learn.
streamOption - Variable in class moa.tasks.EvaluateInterleavedTestThenTrain
streamOption - Variable in class moa.tasks.EvaluateModel
streamOption - Variable in class moa.tasks.EvaluateModelRegression
streamOption - Variable in class moa.tasks.EvaluatePeriodicHeldOutTest
streamOption - Variable in class moa.tasks.EvaluatePrequential
streamOption - Variable in class moa.tasks.EvaluatePrequentialRegression
streamOption - Variable in class moa.tasks.LearnModel
streamOption - Variable in class moa.tasks.LearnModelRegression
streamOption - Variable in class moa.tasks.MeasureStreamSpeed
streamOption - Variable in class moa.tasks.WriteStreamToARFFFile
StreamOutlierPanel - Class in moa.gui.visualization
StreamOutlierPanel(Color) - Constructor for class moa.gui.visualization.StreamOutlierPanel
streamPanel - Variable in class moa.gui.visualization.ClusterPanel
streamPanel - Variable in class moa.gui.visualization.OutlierPanel
StreamPanel - Class in moa.gui.visualization
StreamPanel() - Constructor for class moa.gui.visualization.StreamPanel: Creates new form StreamPanel
streamParameterOption - Variable in class moa.tasks.RunStreamTasks
streamPos - Variable in class moa.streams.CachedInstancesStream
StringOption - Class in moa.options: String option.
StringOption(String, char, String, String) - Constructor for class moa.options.StringOption
StringOptionEditComponent - Class in moa.gui: An OptionEditComponent that lets the user edit a string option.
StringOptionEditComponent(Option) - Constructor for class moa.gui.StringOptionEditComponent
StringUtils - Class in moa.core: Class implementing some string utility methods.
StringUtils() - Constructor for class moa.core.StringUtils
stripPackagePrefix(String, Class<?>) - Static method in class moa.options.AbstractClassOption: Gets the class name without its package name prefix.
subtractValues(DoubleVector) - Method in class moa.core.DoubleVector
subtractValues(double[]) - Method in class moa.core.DoubleVector
subtreeDepth() - Method in class moa.classifiers.trees.HoeffdingOptionTree.Node
subtreeDepth() - Method in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
subtreeDepth() - Method in class moa.classifiers.trees.HoeffdingTree.Node
subtreeDepth() - Method in class moa.classifiers.trees.HoeffdingTree.SplitNode
sum - Variable in class moa.classifiers.rules.functions.TargetMean
sum - Variable in class moa.evaluation.WindowClassificationPerformanceEvaluator.Estimator
sum - Variable in class moa.evaluation.WindowRegressionPerformanceEvaluator.Estimator
sumAbsolutError - Variable in class moa.classifiers.rules.driftdetection.PageHinkleyTest
summary - Variable in class moa.core.GreenwaldKhannaQuantileSummary
sumOfAbsErrors - Variable in class moa.classifiers.trees.FIMTDD.Node
sumOfSquares - Variable in class moa.classifiers.trees.FIMTDD.FIMTDDPerceptron
sumOfSquares - Variable in class moa.classifiers.trees.FIMTDD.Node
sumOfValues - Variable in class moa.classifiers.trees.FIMTDD.FIMTDDPerceptron
sumOfValues - Variable in class moa.classifiers.trees.FIMTDD.Node
sumOfValues() - Method in class moa.core.DoubleVector
sumRatings - Variable in class moa.recommender.rc.data.impl.MemRecommenderData
sumTarget - Variable in class moa.evaluation.BasicRegressionPerformanceEvaluator
Supervised - Variable in class moa.classifiers.rules.RuleClassifier
supportsCustomEditor() - Method in class weka.gui.MOAClassOptionEditor: Returns true because we do support a custom editor.
suppressHeaderOption - Variable in class moa.tasks.WriteStreamToARFFFile
suppressIrrelevantAttributesOption - Variable in class moa.streams.generators.LEDGenerator
switchedAlternateTrees - Variable in class moa.classifiers.trees.HoeffdingAdaptiveTree
swms - Variable in class moa.classifiers.meta.OzaBoost
swms - Variable in class moa.classifiers.meta.OzaBoostAdwin

T

targetFunctionValue(int, int, Point[], Point[]) - Method in class moa.clusterers.streamkm.StreamKM: computes the target function for the given pointarray points[] (of size n) with the given array of centres centres[] (of size k)
targetMean - Variable in class moa.classifiers.rules.core.RuleActiveRegressionNode
TargetMean - Class in moa.classifiers.rules.functions
TargetMean(TargetMean) - Constructor for class moa.classifiers.rules.functions.TargetMean
TargetMean() - Constructor for class moa.classifiers.rules.functions.TargetMean
task - Variable in class moa.tasks.RunStreamTasks
task - Variable in class moa.tasks.RunTasks
Task - Interface in moa.tasks: Interface representing a task.
taskCompleted(TaskThread) - Method in interface moa.tasks.TaskCompletionListener: The method to perform when the task finishes.
TaskCompletionListener - Interface in moa.tasks: Interface representing a listener for the task in TaskThread to be completed.
taskDescField - Variable in class moa.gui.conceptdrift.CDTaskManagerPanel
taskDescField - Variable in class moa.gui.RegressionTaskManagerPanel
taskDescField - Variable in class moa.gui.TaskManagerPanel
taskEndTime - Variable in class moa.tasks.TaskThread
TaskLauncher - Class in moa.gui: The old main class for the MOA gui, now the main class is GUI.
TaskLauncher() - Constructor for class moa.gui.TaskLauncher
taskList - Variable in class moa.gui.conceptdrift.CDTaskManagerPanel
taskList - Variable in class moa.gui.RegressionTaskManagerPanel
taskList - Variable in class moa.gui.TaskManagerPanel
taskManagerPanel - Variable in class moa.gui.ClassificationTabPanel
taskManagerPanel - Variable in class moa.gui.ConceptDriftTabPanel
taskManagerPanel - Variable in class moa.gui.RegressionTabPanel
taskManagerPanel - Variable in class moa.gui.TaskLauncher
TaskManagerPanel - Class in moa.gui: This panel displays the running tasks.
TaskManagerPanel() - Constructor for class moa.gui.TaskManagerPanel
taskManagerPanel - Variable in class moa.gui.TaskTextViewerPanel
TaskManagerPanel.ProgressCellRenderer - Class in moa.gui
TaskManagerPanel.ProgressCellRenderer() - Constructor for class moa.gui.TaskManagerPanel.ProgressCellRenderer
TaskManagerPanel.TaskTableModel - Class in moa.gui
TaskManagerPanel.TaskTableModel() - Constructor for class moa.gui.TaskManagerPanel.TaskTableModel
TaskMonitor - Interface in moa.tasks: Interface representing a task monitor.
taskMonitor - Variable in class moa.tasks.TaskThread
taskOption - Variable in class moa.tasks.RunStreamTasks
taskOption - Variable in class moa.tasks.RunTasks
taskSelectionChanged() - Method in class moa.gui.conceptdrift.CDTaskManagerPanel
taskSelectionChanged() - Method in class moa.gui.RegressionTaskManagerPanel
taskSelectionChanged() - Method in class moa.gui.TaskManagerPanel
taskShouldAbort() - Method in class moa.tasks.NullMonitor
taskShouldAbort() - Method in class moa.tasks.StandardTaskMonitor
taskShouldAbort() - Method in interface moa.tasks.TaskMonitor: Gets whether the task should abort.
taskStartTime - Variable in class moa.tasks.TaskThread
taskTable - Variable in class moa.gui.conceptdrift.CDTaskManagerPanel
taskTable - Variable in class moa.gui.RegressionTaskManagerPanel
taskTable - Variable in class moa.gui.TaskManagerPanel
taskTableModel - Variable in class moa.gui.conceptdrift.CDTaskManagerPanel
taskTableModel - Variable in class moa.gui.RegressionTaskManagerPanel
taskTableModel - Variable in class moa.gui.TaskManagerPanel
TaskTextViewerPanel - Class in moa.gui: This panel displays text.
TaskTextViewerPanel() - Constructor for class moa.gui.TaskTextViewerPanel
TaskTextViewerPanel(PreviewPanel.TypePanel, CDTaskManagerPanel) - Constructor for class moa.gui.TaskTextViewerPanel
TaskThread - Class in moa.tasks: Task Thread.
TaskThread(Task) - Constructor for class moa.tasks.TaskThread
TaskThread(Task, ObjectRepository) - Constructor for class moa.tasks.TaskThread
TaskThread.Status - Enum in moa.tasks
tau_size - Variable in class moa.classifiers.meta.ADACC: Size of the evaluation window to compute the stability index
tauSizeOption - Variable in class moa.classifiers.meta.ADACC: Evaluation window for the stability index computation
TemporallyAugmentedClassifier - Class in moa.classifiers.meta: Include labels of previous instances into the training data
TemporallyAugmentedClassifier() - Constructor for class moa.classifiers.meta.TemporallyAugmentedClassifier
Test - Class in moa.clusterers.outliers.AbstractC
Test() - Constructor for class moa.clusterers.outliers.AbstractC.Test
Test - Class in moa.clusterers.outliers.Angiulli
Test() - Constructor for class moa.clusterers.outliers.Angiulli.Test
Test - Class in moa.clusterers.outliers.MCOD
Test() - Constructor for class moa.clusterers.outliers.MCOD.Test
Test - Class in moa.clusterers.outliers.SimpleCOD
Test() - Constructor for class moa.clusterers.outliers.SimpleCOD.Test
testSizeOption - Variable in class moa.tasks.EvaluatePeriodicHeldOutTest
TestSpeed - Class in moa.clusterers.outliers
TestSpeed() - Constructor for class moa.clusterers.outliers.TestSpeed
textArea - Variable in class moa.gui.TaskTextViewerPanel
textArea - Variable in class moa.gui.TextViewerPanel
textField - Variable in class moa.gui.ClassOptionEditComponent
textField - Variable in class moa.gui.ClassOptionWithNamesEditComponent
textField - Variable in class moa.gui.FileOptionEditComponent
textField - Variable in class moa.gui.WEKAClassOptionEditComponent
textViewerPanel - Variable in class moa.gui.PreviewPanel
TextViewerPanel - Class in moa.gui: This panel displays text.
TextViewerPanel() - Constructor for class moa.gui.TextViewerPanel
theBestAttributes(Instance, AutoExpandVector<AttributeClassObserver>) - Method in class moa.classifiers.rules.RuleClassifier
theta - Variable in class moa.classifiers.meta.OnlineSmoothBoost
theta_diff - Variable in class moa.classifiers.meta.ADACC: Threshold values for the stability index and concept equivalence
theta_stab - Variable in class moa.classifiers.meta.ADACC: Threshold values for the stability index and concept equivalence
threshholdOption - Variable in class moa.clusterers.outliers.AnyOut.AnyOutCore
threshold - Variable in class moa.classifiers.rules.core.Rule.Builder
threshold(double) - Method in class moa.classifiers.rules.core.Rule.Builder
threshold - Variable in class moa.classifiers.rules.driftdetection.PageHinkleyTest
tieThresholdOption - Variable in class moa.classifiers.rules.AbstractAMRules
tieThresholdOption - Variable in class moa.classifiers.rules.RuleClassifier
tieThresholdOption - Variable in class moa.classifiers.trees.FIMTDD
tieThresholdOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree
tieThresholdOption - Variable in class moa.classifiers.trees.HoeffdingTree
tieThresholdOption - Variable in class moa.classifiers.trees.ORTO
time - Variable in class moa.classifiers.lazy.kNNwithPAWandADWIN
timeLimitOption - Variable in class moa.tasks.EvaluateConceptDrift
timeLimitOption - Variable in class moa.tasks.EvaluateInterleavedChunks: Allows to define the maximum number of seconds to test/train for (-1 = no limit).
timeLimitOption - Variable in class moa.tasks.EvaluateInterleavedTestThenTrain
timeLimitOption - Variable in class moa.tasks.EvaluatePrequential
timeLimitOption - Variable in class moa.tasks.EvaluatePrequentialRegression
timeStamp - Variable in class moa.classifiers.lazy.kNNwithPAWandADWIN
Timestamp - Class in moa.clusterers.denstream
Timestamp(long) - Constructor for class moa.clusterers.denstream.Timestamp
Timestamp() - Constructor for class moa.clusterers.denstream.Timestamp
timeStamp - Variable in class moa.clusterers.outliers.MCOD.MCODBase.EventItem
timeStamp - Variable in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase.EventItem
timestamp - Variable in class moa.gui.visualization.DataPoint
timeWindowOption - Variable in class moa.clusterers.ClusterGenerator
timeWindowOption - Variable in class moa.clusterers.clustream.Clustream
timeWindowOption - Variable in class moa.clusterers.clustream.WithKmeans
TimingUtils - Class in moa.core: Class implementing some time utility methods.
TimingUtils() - Constructor for class moa.core.TimingUtils
toCluster() - Method in class moa.clusterers.streamkm.Point
toCommandLine(MOAObject) - Static method in class weka.core.MOAUtils: Returs the commandline for the given object.
toggleRunMode() - Method in class moa.gui.clustertab.ClusteringSetupTab
toggleRunMode() - Method in class moa.gui.outliertab.OutlierSetupTab
toggleVisualizer(boolean) - Method in class moa.gui.clustertab.ClusteringVisualTab
toggleVisualizer(boolean) - Method in class moa.gui.outliertab.OutlierVisualTab
toIntArray(Instance, int) - Static method in class moa.core.utils.EvalUtils: Convert Instance to bit array.
toStream - Variable in class moa.streams.CachedInstancesStream
toString() - Method in class moa.AbstractMOAObject: Returns a description of the object.
toString() - Method in class moa.classifiers.functions.SGD: Prints out the classifier.
toString() - Method in class moa.classifiers.functions.SGDMultiClass: Prints out the classifier.
toString() - Method in class moa.classifiers.functions.SPegasos: Prints out the classifier.
toString() - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Returns an empty string.
toString() - Method in class moa.classifiers.meta.TemporallyAugmentedClassifier
toString() - Method in class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
toString() - Method in class moa.clusterers.outliers.AnyOut.util.DataObject: Returns a String representation of the point.
toString() - Method in class moa.clusterers.outliers.AnyOut.util.DataSet: Returns a String representation of all the DataObjects in the code as a list of the representation implemented for these.
toString() - Method in class moa.evaluation.MembershipMatrix
toString() - Method in class moa.recommender.dataset.impl.FlixsterDataset
toString() - Method in class moa.recommender.dataset.impl.JesterDataset
toString() - Method in class moa.recommender.dataset.impl.MovielensDataset
toString() - Method in class weka.classifiers.meta.MOA: Returns a string representation of the model.
total() - Method in class moa.evaluation.WindowClassificationPerformanceEvaluator.Estimator
total() - Method in class moa.evaluation.WindowRegressionPerformanceEvaluator.Estimator
TOTAL_ATTRIBUTES_INCLUDING_NOISE - Static variable in class moa.streams.generators.WaveformGenerator
total_c - Variable in class moa.classifiers.core.driftdetection.HDDM_A_Test
total_n - Variable in class moa.classifiers.core.driftdetection.HDDM_A_Test
totalCacheInstances - Variable in class moa.streams.filters.CacheFilter
totalDelay - Variable in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
totalSize(Instance) - Method in class moa.classifiers.bayes.NaiveBayesMultinomial
totalSize() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.MyHeap: returns the total size.
totalWeightObserved - Variable in class moa.classifiers.core.attributeclassobservers.NominalAttributeClassObserver
TotalweightObserved - Variable in class moa.evaluation.EWMAClassificationPerformanceEvaluator
TotalweightObserved - Variable in class moa.evaluation.FadingFactorClassificationPerformanceEvaluator
TotalweightObserved - Variable in class moa.evaluation.WindowClassificationPerformanceEvaluator
TotalweightObserved - Variable in class moa.evaluation.WindowRegressionPerformanceEvaluator
totalWeightOfClassObservations() - Method in class moa.classifiers.core.attributeclassobservers.NominalAttributeClassObserver
totalWeightOfClassObservations() - Method in class moa.classifiers.core.attributeclassobservers.NullAttributeClassObserver
train(DataSet) - Method in class moa.clusterers.outliers.AnyOut.AnyOutCore
train() - Method in class moa.recommender.predictor.BaselinePredictor
train() - Method in class moa.recommender.predictor.BRISMFPredictor
train() - Method in interface moa.recommender.predictor.RatingPredictor
train() - Method in class moa.recommender.rc.predictor.impl.BaselinePredictor
train() - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
train() - Method in interface moa.recommender.rc.predictor.RatingPredictor
trainAndClassify(Instance) - Method in class moa.classifiers.meta.DACC: Receives a training instance from the stream and updates the adaptive classifiers accordingly
trainingHasStarted() - Method in class moa.classifiers.AbstractClassifier
trainingHasStarted() - Method in interface moa.classifiers.Classifier: Gets whether training has started.
trainingHasStarted() - Method in class moa.clusterers.AbstractClusterer
trainingHasStarted() - Method in interface moa.clusterers.Clusterer
trainingSetSizeOption - Variable in class moa.clusterers.outliers.AnyOut.AnyOutCore
trainingWeightSeenByModel - Variable in class moa.classifiers.AbstractClassifier: Sum of the weights of the instances trained by this model
trainingWeightSeenByModel() - Method in class moa.classifiers.AbstractClassifier
trainingWeightSeenByModel() - Method in interface moa.classifiers.Classifier: Gets the sum of the weights of the instances that have been used by this classifier during the training in trainOnInstance
trainingWeightSeenByModel - Variable in class moa.clusterers.AbstractClusterer
trainingWeightSeenByModel() - Method in class moa.clusterers.AbstractClusterer
trainingWeightSeenByModel() - Method in interface moa.clusterers.Clusterer
trainItem(int) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
trainItem(int, int) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
trainItem(int, List<Integer>, List<Double>) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
trainItem(int, List<Integer>, List<Double>, int) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
trainItemFeats(int, List<Integer>, List<Double>, int) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
trainOnInstance(Instance) - Method in class moa.classifiers.AbstractClassifier
trainOnInstance(Instance) - Method in interface moa.classifiers.Classifier: Trains this classifier incrementally using the given instance.
trainOnInstance(Instance) - Method in class moa.clusterers.AbstractClusterer
trainOnInstance(Instance) - Method in interface moa.clusterers.Clusterer
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.AbstractClassifier: Trains this classifier incrementally using the given instance.

The reason for ...Impl methods: ease programmer burden by not requiring them to remember calls to super in overridden methods.
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.active.ActiveClassifier
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.bayes.NaiveBayes
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.bayes.NaiveBayesMultinomial: Trains the classifier with the given instance.
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.drift.DriftDetectionMethodClassifier
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.functions.MajorityClass
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.functions.NoChange
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.functions.Perceptron
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.functions.SGD: Trains the classifier with the given instance.
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.functions.SGDMultiClass: Trains the classifier with the given instance.
trainOnInstanceImpl(Instance, int) - Method in class moa.classifiers.functions.SGDMultiClass
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.functions.SPegasos: Trains the classifier with the given instance.
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.lazy.kNN
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.lazy.kNNwithPAW
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.lazy.kNNwithPAWandADWIN
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.meta.AccuracyUpdatedEnsemble
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.meta.AccuracyWeightedEnsemble
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.meta.ADACC
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.meta.DACC
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.meta.LeveragingBag
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.meta.LimAttClassifier
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.meta.OCBoost
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.meta.OnlineSmoothBoost
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.meta.OzaBag
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.meta.OzaBagAdwin
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.meta.OzaBagASHT
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.meta.OzaBoost
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.meta.OzaBoostAdwin
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.meta.RandomRules
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.meta.TemporallyAugmentedClassifier
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.meta.WeightedMajorityAlgorithm
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.meta.WEKAClassifier
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.multilabel.MajorityLabelset
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.multilabel.MEKAClassifier
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.multilabel.meta.MLOzaBagAdwin
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.rules.AbstractAMRules
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.rules.functions.FadingTargetMean
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.rules.functions.Perceptron: Update the model using the provided instance
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.rules.functions.TargetMean
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.rules.RuleClassifier
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.trees.ASHoeffdingTree
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.trees.DecisionStump
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.trees.FIMTDD: Method for updating (training) the model using a new instance
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.trees.HoeffdingOptionTree
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.trees.HoeffdingTree
trainOnInstanceImpl(Instance, ORTO) - Method in class moa.classifiers.trees.ORTO.ORTOPerceptron: Update the model using the provided instance
trainOnInstanceImpl(Instance) - Method in class moa.classifiers.trees.ORTO: Method for updating (training) the model using a new instance
trainOnInstanceImpl(Instance) - Method in class moa.clusterers.AbstractClusterer
trainOnInstanceImpl(Instance) - Method in class moa.clusterers.ClusterGenerator
trainOnInstanceImpl(Instance) - Method in class moa.clusterers.clustream.Clustream
trainOnInstanceImpl(Instance) - Method in class moa.clusterers.clustream.WithKmeans
trainOnInstanceImpl(Instance) - Method in class moa.clusterers.clustree.ClusTree
trainOnInstanceImpl(Instance) - Method in class moa.clusterers.CobWeb: Adds an instance to the clusterer.
trainOnInstanceImpl(Instance) - Method in class moa.clusterers.denstream.WithDBSCAN
trainOnInstanceImpl(Instance) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
trainOnInstanceImpl(Instance) - Method in class moa.clusterers.streamkm.StreamKM
trainOnInstanceImpl(Instance) - Method in class moa.clusterers.WekaClusteringAlgorithm
trainOnInstanceImpl(Instance) - Method in class moa.learners.ChangeDetectorLearner
trainOnInstanceImplPerceptron(int, int, double[][]) - Method in class moa.classifiers.meta.LimAttClassifier
trainSizeOption - Variable in class moa.tasks.EvaluatePeriodicHeldOutTest
trainTimeOption - Variable in class moa.tasks.EvaluatePeriodicHeldOutTest
trainUser(int, List<Integer>, List<Double>, int) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
trainUser(int, int) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
trainUser(int, List<Integer>, List<Double>) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
trainUser(int) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
trainUserFeats(List<Integer>, List<Double>, int) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
treeCoreset - Variable in class moa.clusterers.streamkm.BucketManager
TreeCoreset - Class in moa.clusterers.streamkm
TreeCoreset() - Constructor for class moa.clusterers.streamkm.TreeCoreset
TreeCoreset.treeNode - Class in moa.clusterers.streamkm: datastructure representing a node within a tree
TreeCoreset.treeNode(int, Point[], Point, TreeCoreset.treeNode) - Constructor for class moa.clusterers.streamkm.TreeCoreset.treeNode
TreeCoreset.treeNode(Point[], Point[], int, int, Point, int) - Constructor for class moa.clusterers.streamkm.TreeCoreset.treeNode: initalizes root as a treenode with the union of setA and setB as pointset and centre as centre
treeRandomSeedOption - Variable in class moa.streams.generators.RandomTreeGenerator
treeRoot - Variable in class moa.classifiers.trees.FIMTDD
treeRoot - Variable in class moa.classifiers.trees.HoeffdingOptionTree
treeRoot - Variable in class moa.classifiers.trees.HoeffdingTree
treeRoot - Variable in class moa.classifiers.trees.ORTO
treeRoot - Variable in class moa.streams.generators.RandomTreeGenerator
trueClass - Variable in class moa.evaluation.CMM_GTAnalysis.CMMPoint: true class label
tryToExpand(double, double) - Method in class moa.classifiers.rules.core.Rule: Try to Expand method.
tryToExpand(double, double) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
tryToExpand(double, double) - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
type - Variable in class moa.gui.visualization.PointPanel
TYPE_CLUSTERED - Variable in class moa.gui.visualization.PointPanel
TYPE_PLAIN - Variable in class moa.gui.visualization.PointPanel
typePanel - Variable in class moa.gui.TaskTextViewerPanel

U

UniformWeightedVote - Class in moa.classifiers.rules.core.voting: UniformWeightedVote class for weighted votes based on estimates of errors.
UniformWeightedVote() - Constructor for class moa.classifiers.rules.core.voting.UniformWeightedVote
univariateAnomalyprobabilityThresholdOption - Variable in class moa.classifiers.rules.AbstractAMRules
unorderedRulesOption - Variable in class moa.classifiers.rules.AbstractAMRules
unset() - Method in class moa.options.FlagOption
Unsupervised - Variable in class moa.classifiers.rules.RuleClassifier
Updatable - Interface in moa.recommender.rc.utils
updatables - Variable in class moa.recommender.rc.data.AbstractRecommenderData
update(Instance) - Method in interface moa.classifiers.lazy.neighboursearch.DistanceFunction: Update the distance function (if necessary) for the newly added instance.
update(Instance) - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Adds one instance to the KDTree.
update(Instance) - Method in class moa.classifiers.lazy.neighboursearch.LinearNNSearch: Updates the LinearNNSearch to cater for the new added instance.
update(Instance) - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch: Updates the NearNeighbourSearch algorithm for the new added instance.
update(Instance) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Update the distance function (if necessary) for the newly added instance.
update(double) - Method in class moa.classifiers.rules.driftdetection.PageHinkleyFading
update(double) - Method in class moa.classifiers.rules.driftdetection.PageHinkleyTest
update() - Method in class moa.gui.clustertab.ClusteringVisualEvalPanel
update() - Method in class moa.gui.outliertab.OutlierVisualEvalPanel
updateAccumulatedError(Instance) - Method in class moa.classifiers.rules.functions.TargetMean
updateAutoRefreshTimer() - Method in class moa.gui.PreviewPanel
updateCanvas() - Method in class moa.gui.visualization.GraphCanvas
updateCanvas(boolean) - Method in class moa.gui.visualization.GraphCanvas
updateChangeDetection(double) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
updateClassifier(Instance) - Method in class weka.classifiers.meta.MOA: Updates a classifier using the given instance.
updateCount(Instance, int) - Method in class moa.classifiers.multilabel.MajorityLabelset
updateDistance(double, double) - Method in class moa.classifiers.lazy.neighboursearch.EuclideanDistance: Updates the current distance calculated so far with the new difference between two attributes.
updateDistance(double, double) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Updates the current distance calculated so far with the new difference between two attributes.
updateEstimations() - Method in class moa.classifiers.core.driftdetection.HDDM_A_Test
updateEvaluationWindow(int, int) - Method in class moa.classifiers.meta.DACC: Updates the evaluation window of a classifier and returns the updated weight value.
updateInfo(String) - Method in class moa.gui.visualization.InfoPanel
updateLocation() - Method in class moa.gui.visualization.ClusterPanel
updateLocation() - Method in class moa.gui.visualization.OutlierPanel
updateLocation() - Method in class moa.gui.visualization.PointPanel
UpdateMaxMemUsage() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
updateNewItem(int, List<Integer>, List<Double>) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
updateNewItem(int, List<Integer>, List<Double>) - Method in interface moa.recommender.rc.utils.Updatable
updateNewUser(int, List<Integer>, List<Double>) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
updateNewUser(int, List<Integer>, List<Double>) - Method in interface moa.recommender.rc.utils.Updatable
updateOptionCount(HoeffdingOptionTree.SplitNode, HoeffdingOptionTree) - Method in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
updateOptionCountBelow(int, HoeffdingOptionTree) - Method in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
updatePageHinckleyTest(double) - Method in class moa.classifiers.rules.core.Rule
updatePageHinckleyTest(double) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
updatePerceptron(Instance, FIMTDD) - Method in class moa.classifiers.trees.FIMTDD.FIMTDDPerceptron: Update the model using the provided instance
updateRanges(Instance, int, double[][]) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Updates the minimum and maximum and width values for all the attributes based on a new instance.
updateRanges(Instance, double[][]) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Updates the ranges given a new instance.
updateRanges(Instance) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Update the ranges if a new instance comes.
updateRangesFirst(Instance, int, double[][]) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: Used to initialize the ranges.
updateRemoveItem(int) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
updateRemoveItem(int) - Method in interface moa.recommender.rc.utils.Updatable
updateRemoveRating(int, int) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
updateRemoveRating(int, int) - Method in interface moa.recommender.rc.utils.Updatable
updateRemoveUser(int) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
updateRemoveUser(int) - Method in interface moa.recommender.rc.utils.Updatable
updateRuleAttribStatistics(Instance, RuleClassification, int) - Method in class moa.classifiers.rules.RuleClassifier
updateSetRating(int, int, double) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
updateSetRating(int, int, double) - Method in interface moa.recommender.rc.utils.Updatable
updateStatistics(Instance) - Method in class moa.classifiers.rules.core.Rule
updateStatistics(Instance) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
updateStatistics(Instance) - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
UpdateStatistics(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.Angiulli.STORMBase
updateTooltip() - Method in class moa.gui.visualization.ClusterPanel
updateTooltip() - Method in class moa.gui.visualization.OutlierPanel
updateWeight(int, double) - Method in class moa.gui.visualization.DataPoint
updateWeights(Instance, double) - Method in class moa.classifiers.rules.functions.Perceptron
updateWeights(Instance, double, FIMTDD) - Method in class moa.classifiers.trees.FIMTDD.FIMTDDPerceptron
upheap() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.MyHeap: performs upheap operation for the heap to maintian its properties.
upperBound - Variable in class moa.classifiers.core.attributeclassobservers.VFMLNumericAttributeClassObserver.Bin
useBaggingOption - Variable in class moa.classifiers.meta.RandomRules
UseMeanScoreOption - Variable in class moa.clusterers.outliers.AnyOut.AnyOutCore
useMicroGT - Variable in class moa.gui.BatchCmd
usePerceptron - Variable in class moa.classifiers.rules.core.Rule.Builder
userExists(int) - Method in class moa.recommender.rc.data.impl.MemRecommenderData
userExists(int) - Method in interface moa.recommender.rc.data.RecommenderData
userFeature - Variable in class moa.recommender.rc.predictor.impl.BRISMFPredictor
userID - Variable in class moa.recommender.rc.utils.Rating
usersStats - Variable in class moa.recommender.rc.data.impl.MemRecommenderData
useWeightOption - Variable in class moa.classifiers.meta.OzaBagASHT
Utils - Class in moa.clusterers.outliers.utils.mtree.utils: Some utilities.

V

v - Variable in class moa.core.GreenwaldKhannaQuantileSummary.Tuple
validate() - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance: performs the initializations if necessary.
validate() - Method in class moa.gui.conceptdrift.CDTaskManagerPanel.ProgressCellRenderer
validate() - Method in class moa.gui.RegressionTaskManagerPanel.ProgressCellRenderer
validate() - Method in class moa.gui.TaskManagerPanel.ProgressCellRenderer
ValorTargetRule - Variable in class moa.classifiers.rules.RuleClassification
value - Variable in class moa.core.Measurement
valueIsSmallerEqual(Instance, int, double) - Method in class moa.classifiers.lazy.neighboursearch.EuclideanDistance: Returns true if the value of the given dimension is smaller or equal the value to be compared with.
valueOf(String) - Static method in enum moa.clusterers.outliers.MCOD.ISBIndex.ISBNode.NodeType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum moa.gui.PreviewPanel.TypePanel: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum moa.tasks.Plot.LegendLocation: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum moa.tasks.Plot.LegendType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum moa.tasks.Plot.PlotStyle: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum moa.tasks.Plot.Terminal: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum moa.tasks.TaskThread.Status: Returns the enum constant of this type with the specified name.
values() - Static method in enum moa.clusterers.outliers.MCOD.ISBIndex.ISBNode.NodeType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum moa.gui.PreviewPanel.TypePanel: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum moa.tasks.Plot.LegendLocation: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum moa.tasks.Plot.LegendType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum moa.tasks.Plot.PlotStyle: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum moa.tasks.Plot.Terminal: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum moa.tasks.TaskThread.Status: Returns an array containing the constants of this enum type, in the order they are declared.
VarianceReductionSplitCriterion - Class in moa.classifiers.core.splitcriteria
VarianceReductionSplitCriterion() - Constructor for class moa.classifiers.core.splitcriteria.VarianceReductionSplitCriterion
varianceSum - Variable in class moa.core.GaussianEstimator
Vector - Class in moa.recommender.rc.utils
Vector() - Constructor for class moa.recommender.rc.utils.Vector
verboseOption - Variable in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble: Determines whether additional information should be sent to the output.
VerboseToConsole(Instance) - Method in class moa.classifiers.rules.AbstractAMRules
VerbosityOption - Variable in class moa.classifiers.rules.AbstractAMRules
versionString - Static variable in class moa.core.Globals
VFMLNumericAttributeClassObserver - Class in moa.classifiers.core.attributeclassobservers: Class for observing the class data distribution for a numeric attribute as in VFML.
VFMLNumericAttributeClassObserver() - Constructor for class moa.classifiers.core.attributeclassobservers.VFMLNumericAttributeClassObserver
VFMLNumericAttributeClassObserver.Bin - Class in moa.classifiers.core.attributeclassobservers
VFMLNumericAttributeClassObserver.Bin() - Constructor for class moa.classifiers.core.attributeclassobservers.VFMLNumericAttributeClassObserver.Bin
votes - Variable in class moa.classifiers.rules.core.voting.AbstractErrorWeightedVote
votingTypeOption - Variable in class moa.classifiers.rules.AMRulesRegressor

W

waitWinFullOption - Variable in class moa.clusterers.outliers.AbstractC.AbstractC
waitWinFullOption - Variable in class moa.clusterers.outliers.Angiulli.STORMBase
warningConfidence - Variable in class moa.classifiers.core.driftdetection.HDDM_W_Test
warningConfidenceOption - Variable in class moa.classifiers.core.driftdetection.HDDM_A_Test
warningConfidenceOption - Variable in class moa.classifiers.core.driftdetection.HDDM_W_Test
warningDetected - Variable in class moa.classifiers.drift.DriftDetectionMethodClassifier
WaveformGenerator - Class in moa.streams.generators: Stream generator for the problem of predicting one of three waveform types.
WaveformGenerator() - Constructor for class moa.streams.generators.WaveformGenerator
WaveformGeneratorDrift - Class in moa.streams.generators: Stream generator for the problem of predicting one of three waveform types with drift.
WaveformGeneratorDrift() - Constructor for class moa.streams.generators.WaveformGeneratorDrift
webAddress - Static variable in class moa.core.Globals
weightAttribute - Variable in class moa.classifiers.functions.Perceptron
weightAttribute - Variable in class moa.classifiers.meta.LimAttClassifier
weightAttribute - Variable in class moa.classifiers.rules.functions.Perceptron
weightAttribute - Variable in class moa.classifiers.rules.RuleClassification
weightAttribute - Variable in class moa.classifiers.trees.FIMTDD.FIMTDDPerceptron
weightAttribute - Variable in class moa.classifiers.trees.ORTO.ORTOPerceptron
weightComparator - Static variable in class moa.classifiers.meta.AccuracyWeightedEnsemble: Simple weight comparator.
weightCorrect - Variable in class moa.evaluation.BasicClassificationPerformanceEvaluator
weightCorrect - Variable in class moa.evaluation.BasicClusteringPerformanceEvaluator
weightCorrect - Variable in class moa.evaluation.EWMAClassificationPerformanceEvaluator
weightCorrect - Variable in class moa.evaluation.FadingFactorClassificationPerformanceEvaluator
weightCorrect - Variable in class moa.evaluation.WindowClassificationPerformanceEvaluator
weightCorrectNoChangeClassifier - Variable in class moa.evaluation.WindowClassificationPerformanceEvaluator
WeightedMajorityAlgorithm - Class in moa.classifiers.meta: Weighted majority algorithm for data streams.
WeightedMajorityAlgorithm() - Constructor for class moa.classifiers.meta.WeightedMajorityAlgorithm
weightedMax(Instance) - Method in class moa.classifiers.rules.RuleClassifier
weightedMaxNB(Instance) - Method in class moa.classifiers.rules.RuleClassifierNBayes
weightedSum(Instance) - Method in class moa.classifiers.rules.RuleClassifier
weightedSumNB(Instance) - Method in class moa.classifiers.rules.RuleClassifierNBayes
weightObserved - Variable in class moa.evaluation.BasicClassificationPerformanceEvaluator
weightObserved - Variable in class moa.evaluation.BasicClusteringPerformanceEvaluator
weightObserved - Variable in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
weightObserved - Variable in class moa.evaluation.BasicRegressionPerformanceEvaluator
weightObserved - Variable in class moa.evaluation.WindowClassificationPerformanceEvaluator
weightObserved - Variable in class moa.evaluation.WindowRegressionPerformanceEvaluator
weightOfObservedMissingValues() - Method in class moa.classifiers.core.attributeclassobservers.NominalAttributeClassObserver
weightOfObservedMissingValues() - Method in class moa.classifiers.core.attributeclassobservers.NullAttributeClassObserver
weights - Variable in class moa.classifiers.meta.AccuracyUpdatedEnsemble: The weights of stored classifiers.
weights - Variable in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble: The weights of stored classifiers.
weights - Variable in class moa.classifiers.rules.core.voting.AbstractErrorWeightedVote
weights - Variable in class moa.streams.generators.HyperplaneGenerator
weightSeen - Variable in class moa.classifiers.trees.ORTO.InnerNode
weightSeenAtLastSplit - Variable in class moa.classifiers.trees.DecisionStump
weightSeenAtLastSplitEvaluation - Variable in class moa.classifiers.trees.FIMTDD.Node
weightSeenAtLastSplitEvaluation - Variable in class moa.classifiers.trees.HoeffdingOptionTree.ActiveLearningNode
weightSeenAtLastSplitEvaluation - Variable in class moa.classifiers.trees.HoeffdingTree.ActiveLearningNode
weightSeenAtLastSplitEvaluation - Variable in class moa.classifiers.trees.LimAttHoeffdingTree.LimAttLearningNode
weightShrinkOption - Variable in class moa.classifiers.meta.LeveragingBag
weightShrinkOption - Variable in class moa.classifiers.meta.LimAttClassifier
weightSum - Variable in class moa.core.GaussianEstimator
weka() - Method in class moa.gui.visualization.RunOutlierVisualizer
weka() - Method in class moa.gui.visualization.RunVisualizer
weka.classifiers.meta - package weka.classifiers.meta
weka.core - package weka.core
weka.datagenerators.classifiers.classification - package weka.datagenerators.classifiers.classification
weka.gui - package weka.gui
wekaAlgorithmOption - Variable in class moa.clusterers.WekaClusteringAlgorithm
WEKAClassifier - Class in moa.classifiers.meta: Class for using a classifier from WEKA.
WEKAClassifier() - Constructor for class moa.classifiers.meta.WEKAClassifier
WEKAClassOption - Class in moa.options: WEKA class option.
WEKAClassOption(String, char, String, Class<?>, String) - Constructor for class moa.options.WEKAClassOption
WEKAClassOption(String, char, String, Class<?>, String, String) - Constructor for class moa.options.WEKAClassOption
WEKAClassOptionEditComponent - Class in moa.gui: An OptionEditComponent that lets the user edit a WEKA class option.
WEKAClassOptionEditComponent(WEKAClassOption) - Constructor for class moa.gui.WEKAClassOptionEditComponent
WekaClusteringAlgorithm - Class in moa.clusterers
WekaClusteringAlgorithm() - Constructor for class moa.clusterers.WekaClusteringAlgorithm
WekaExplorer - Class in moa.gui.visualization
WekaExplorer(Instances) - Constructor for class moa.gui.visualization.WekaExplorer
widestDim(double[][], double[][]) - Method in class moa.classifiers.lazy.neighboursearch.KDTree: Returns the widest dimension/attribute in a KDTreeNode (widest after normalizing).
widestDim(double[][], double[][]) - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter: Returns the widest dimension.
width - Variable in class moa.classifiers.core.driftdetection.HDDM_W_Test
WIDTH - Static variable in class moa.classifiers.lazy.neighboursearch.KDTree: The index of WIDTH (MAX-MIN) value in attributes' range array.
WIDTH - Static variable in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter: Index of width value (max-min) in an array of attributes' range.
widthInitOption - Variable in class moa.classifiers.meta.WEKAClassifier
widthOption - Variable in class moa.classifiers.meta.WEKAClassifier
widthOption - Variable in class moa.clusterers.streamkm.StreamKM
widthOption - Variable in class moa.evaluation.WindowClassificationPerformanceEvaluator
widthOption - Variable in class moa.evaluation.WindowRegressionPerformanceEvaluator
widthOption - Variable in class moa.streams.ConceptDriftRealStream
widthOption - Variable in class moa.streams.ConceptDriftStream
widthOption - Variable in class moa.tasks.EvaluatePrequential
widthOption - Variable in class moa.tasks.EvaluatePrequentialRegression
window - Variable in class moa.classifiers.lazy.kNN
window - Variable in class moa.evaluation.WindowClassificationPerformanceEvaluator.Estimator
window - Variable in class moa.evaluation.WindowRegressionPerformanceEvaluator.Estimator
window_size - Variable in class moa.gui.visualization.ClusterPanel
window_size - Variable in class moa.gui.visualization.OutlierPanel
window_size - Variable in class moa.gui.visualization.PointPanel
WindowClassificationPerformanceEvaluator - Class in moa.evaluation: Classification evaluator that updates evaluation results using a sliding window.
WindowClassificationPerformanceEvaluator() - Constructor for class moa.evaluation.WindowClassificationPerformanceEvaluator
WindowClassificationPerformanceEvaluator.Estimator - Class in moa.evaluation
WindowClassificationPerformanceEvaluator.Estimator(int) - Constructor for class moa.evaluation.WindowClassificationPerformanceEvaluator.Estimator
windowNodes - Variable in class moa.clusterers.outliers.AbstractC.AbstractCBase
windowNodes - Variable in class moa.clusterers.outliers.Angiulli.STORMBase
windowNodes - Variable in class moa.clusterers.outliers.MCOD.MCODBase
windowNodes - Variable in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
WindowRegressionPerformanceEvaluator - Class in moa.evaluation: Regression evaluator that updates evaluation results using a sliding window.
WindowRegressionPerformanceEvaluator() - Constructor for class moa.evaluation.WindowRegressionPerformanceEvaluator
WindowRegressionPerformanceEvaluator.Estimator - Class in moa.evaluation
WindowRegressionPerformanceEvaluator.Estimator(int) - Constructor for class moa.evaluation.WindowRegressionPerformanceEvaluator.Estimator
windowSize - Variable in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble: Window size.
windowSizeOption - Variable in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble: Chunk size.
windowSizeOption - Variable in class moa.clusterers.outliers.MyBaseOutlierDetector
WithDBSCAN - Class in moa.clusterers.denstream
WithDBSCAN() - Constructor for class moa.clusterers.denstream.WithDBSCAN
WithKmeans - Class in moa.clusterers.clustream
WithKmeans() - Constructor for class moa.clusterers.clustream.WithKmeans
wneg - Variable in class moa.classifiers.meta.OCBoost
workbenchTitle - Static variable in class moa.core.Globals
workclass() - Method in class moa.evaluation.CMM_GTAnalysis.CMMPoint: Retruns the current working label of the cluster the point belongs to.
wpos - Variable in class moa.classifiers.meta.OCBoost
write(int) - Method in class moa.core.SerializeUtils.ByteCountingOutputStream
write(byte[], int, int) - Method in class moa.core.SerializeUtils.ByteCountingOutputStream
write(byte[]) - Method in class moa.core.SerializeUtils.ByteCountingOutputStream
WriteStreamToARFFFile - Class in moa.tasks: Task to output a stream to an ARFF file
WriteStreamToARFFFile() - Constructor for class moa.tasks.WriteStreamToARFFFile
writeToFile(File, Serializable) - Static method in class moa.core.SerializeUtils

X

x_dim - Variable in class moa.gui.visualization.ClusterPanel
x_dim - Variable in class moa.gui.visualization.OutlierPanel
x_dim - Variable in class moa.gui.visualization.PointPanel
xAxisIndex - Variable in class moa.gui.LineGraphViewPanel.PlotLine
xColumnOption - Variable in class moa.tasks.Plot: Index of the csv column from which values for the x-axis should be taken.
XiSum - Variable in class moa.classifiers.rules.RuleClassification
xMax - Variable in class moa.gui.LineGraphViewPanel.PlotLine
xMin - Variable in class moa.gui.LineGraphViewPanel.PlotLine
xTitleOption - Variable in class moa.tasks.Plot: Title of the plots' x-axis.
xUnitOption - Variable in class moa.tasks.Plot: Units displayed next to x-axis values.

Y

y_dim - Variable in class moa.gui.visualization.ClusterPanel
y_dim - Variable in class moa.gui.visualization.OutlierPanel
y_dim - Variable in class moa.gui.visualization.PointPanel
yAxisIndex - Variable in class moa.gui.LineGraphViewPanel.PlotLine
yColumnOption - Variable in class moa.tasks.Plot: Index of the csv column from which values for the y-axis should be taken.
yMax - Variable in class moa.gui.LineGraphViewPanel.PlotLine
yMin - Variable in class moa.gui.LineGraphViewPanel.PlotLine
yTitleOption - Variable in class moa.tasks.Plot: Title of the plots' y-axis.
yUnitOption - Variable in class moa.tasks.Plot: Units displayed next to y-axis values.

_

_check() - Method in class moa.clusterers.outliers.utils.mtree.MTree

A B C D E F G H I J K L M N O P Q R S T U V W X Y _