Index (jaicore-ml-weka 0.2.4 API)

A B C D E F G H I J K L M N O P Q R S T U V W Z
All Classes All Packages

A

AbstractAugmentedSpaceSampler - Class in ai.libs.jaicore.ml.weka.rangequery
AbstractAugmentedSpaceSampler(Instances, Random) - Constructor for class ai.libs.jaicore.ml.weka.rangequery.AbstractAugmentedSpaceSampler
AccessibleRandomTree - Class in ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees: Random Tree extension providing leaf node information of the constructed tree.
AccessibleRandomTree() - Constructor for class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.AccessibleRandomTree
AccessibleRandomTree.AccessibleTree - Class in ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees
AccessibleTree() - Constructor for class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.AccessibleRandomTree.AccessibleTree
activelyTrainWithOneInstance() - Method in class ai.libs.jaicore.ml.weka.ranking.dyad.learner.activelearning.ConfidenceIntervalClusteringBasedActiveDyadRanker
add(FeatureDomain) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.FeatureSpace
addChild(MCTreeNode) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNode
addChild(MCTreeNode) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeLeaf
addChild(FeatureGenerator) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.featuregen.FeatureGeneratorTree
addChild(List<String>, Classifier) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeReD
addChild(List<String>, Classifier) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeReDLeaf
addInstruction(IReconstructionInstruction) - Method in class ai.libs.jaicore.ml.weka.classification.learner.AWekaLearner
addInstruction(IReconstructionInstruction) - Method in class ai.libs.jaicore.ml.weka.dataset.WekaInstances
aggregate(List<Double>) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.aggregation.AggressiveAggregator
aggregate(List<Double>) - Method in interface ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.aggregation.IntervalAggregator
aggregate(List<Double>) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.aggregation.QuantileAggregator
AggressiveAggregator - Class in ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.aggregation: An IntervalAggregator that makes predictions using the minimum of the predictions as the lower bound and the maximum as the upper bound.
AggressiveAggregator() - Constructor for class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.aggregation.AggressiveAggregator
ai.libs.jaicore.ml.weka - package ai.libs.jaicore.ml.weka
ai.libs.jaicore.ml.weka.classification - package ai.libs.jaicore.ml.weka.classification
ai.libs.jaicore.ml.weka.classification.learner - package ai.libs.jaicore.ml.weka.classification.learner
ai.libs.jaicore.ml.weka.classification.learner.reduction - package ai.libs.jaicore.ml.weka.classification.learner.reduction
ai.libs.jaicore.ml.weka.classification.learner.reduction.reducer - package ai.libs.jaicore.ml.weka.classification.learner.reduction.reducer
ai.libs.jaicore.ml.weka.classification.learner.reduction.splitter - package ai.libs.jaicore.ml.weka.classification.learner.reduction.splitter
ai.libs.jaicore.ml.weka.classification.pipeline - package ai.libs.jaicore.ml.weka.classification.pipeline
ai.libs.jaicore.ml.weka.classification.pipeline.featuregen - package ai.libs.jaicore.ml.weka.classification.pipeline.featuregen
ai.libs.jaicore.ml.weka.classification.pipeline.featurepreprocess - package ai.libs.jaicore.ml.weka.classification.pipeline.featurepreprocess
ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.ensemble - package ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.ensemble: A package consisting of ensemble classifiers used in implemented time series classifiers.
ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets - package ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets: This package contains implementations for Shapelet based classifier and training algorithms.
ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees - package ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees
ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.util - package ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.util
ai.libs.jaicore.ml.weka.classification.timeseries.learner.ensemble - package ai.libs.jaicore.ml.weka.classification.timeseries.learner.ensemble
ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets - package ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets
ai.libs.jaicore.ml.weka.dataset - package ai.libs.jaicore.ml.weka.dataset: This package contains classes for weka-specific logics regarding the dataset.
ai.libs.jaicore.ml.weka.preprocessing - package ai.libs.jaicore.ml.weka.preprocessing
ai.libs.jaicore.ml.weka.rangequery - package ai.libs.jaicore.ml.weka.rangequery
ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree - package ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree
ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.aggregation - package ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.aggregation
ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace - package ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace
ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.util - package ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.util
ai.libs.jaicore.ml.weka.ranking.dyad.learner.activelearning - package ai.libs.jaicore.ml.weka.ranking.dyad.learner.activelearning
ai.libs.jaicore.ml.weka.ranking.dyad.learner.zeroshot.util - package ai.libs.jaicore.ml.weka.ranking.dyad.learner.zeroshot.util
ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac - package ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac
ai.libs.jaicore.ml.weka.regression.learner - package ai.libs.jaicore.ml.weka.regression.learner
ALLPAIRS - ai.libs.jaicore.ml.weka.classification.learner.reduction.EMCNodeType
AllPairsTable - Class in ai.libs.jaicore.ml.weka.classification.learner.reduction
AllPairsTable(Instances, Instances, Classifier) - Constructor for class ai.libs.jaicore.ml.weka.classification.learner.reduction.AllPairsTable
ALPHA - Static variable in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm: Predefined alpha parameter used within the calculations.
AMCTreeNode<C extends java.io.Serializable> - Class in ai.libs.jaicore.ml.weka.classification.learner.reduction
AMCTreeNode(List<C>) - Constructor for class ai.libs.jaicore.ml.weka.classification.learner.reduction.AMCTreeNode
apply(Instance) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.featuregen.FeatureGeneratorTree
apply(Instance) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.featuregen.InteractingFeatures
apply(Instance) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.featuregen.PolynomialFeatures
apply(Instance) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.featurepreprocess.Normalization
apply(Instance) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.featurepreprocess.Standardization
apply(Instance) - Method in interface ai.libs.jaicore.ml.weka.classification.pipeline.FeaturePreprocessor
apply(Instance) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.MLSophisticatedPipeline
apply(Instance) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.SupervisedFilterSelector
apply(Instance) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.SuvervisedFilterPreprocessor
apply(Instances) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.featuregen.FeatureGeneratorTree
apply(Instances) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.featuregen.InteractingFeatures
apply(Instances) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.featuregen.PolynomialFeatures
apply(Instances) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.featurepreprocess.Normalization
apply(Instances) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.featurepreprocess.Standardization
apply(Instances) - Method in interface ai.libs.jaicore.ml.weka.classification.pipeline.FeaturePreprocessor
apply(Instances) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.MLSophisticatedPipeline
apply(Instances) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.SupervisedFilterSelector
apply(Instances) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.SuvervisedFilterPreprocessor
apply(Instances) - Method in class ai.libs.jaicore.ml.weka.rangequery.AugSpaceAllPairs
areInstancesEqual(Instance, Instance) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
AugSpaceAllPairs - Class in ai.libs.jaicore.ml.weka.rangequery
AugSpaceAllPairs() - Constructor for class ai.libs.jaicore.ml.weka.rangequery.AugSpaceAllPairs
augSpaceSample() - Method in class ai.libs.jaicore.ml.weka.rangequery.ChooseKAugSpaceSampler
augSpaceSample() - Method in class ai.libs.jaicore.ml.weka.rangequery.ExactIntervalAugSpaceSampler
augSpaceSample() - Method in interface ai.libs.jaicore.ml.weka.rangequery.IAugmentedSpaceSampler: Generates a point in the augmented space from the AugmentedSpaceSampler's precise dataset.
augSpaceSample() - Method in class ai.libs.jaicore.ml.weka.rangequery.KNNAugSpaceSampler
AWekaLearner<P extends org.api4.java.ai.ml.core.evaluation.IPrediction,B extends org.api4.java.ai.ml.core.evaluation.IPredictionBatch> - Class in ai.libs.jaicore.ml.weka.classification.learner
AWekaLearner(String, String[]) - Constructor for class ai.libs.jaicore.ml.weka.classification.learner.AWekaLearner
AWekaLearner(Classifier) - Constructor for class ai.libs.jaicore.ml.weka.classification.learner.AWekaLearner

B

buildClassifier(Instances) - Method in class ai.libs.jaicore.ml.weka.classification.learner.Ensemble
buildClassifier(Instances) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.ConstantClassifier
buildClassifier(Instances) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNode
buildClassifier(Instances) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeLeaf
buildClassifier(Instances) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeReD
buildClassifier(Instances) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeReDLeaf
buildClassifier(Instances) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.reducer.HighProbClassifier
buildClassifier(Instances) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.reducer.ReductionOptimizer
buildClassifier(Instances) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.MLPipeline
buildClassifier(Instances) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.MLSophisticatedPipeline
buildClassifier(Instances) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.ensemble.MajorityConfidenceVote: Builds the ensemble by assessing the classifier weights using a cross validation of each classifier of the ensemble and then training the classifiers using the complete data.
buildClassifier(Instances) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.AccessibleRandomTree
buildGroup(List<ProblemInstance<Instance>>) - Method in class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.ModifiedISACGroupBuilder
buildTree(Instances, double[], int[], double, Random, int, double) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.AccessibleRandomTree.AccessibleTree
buildWekaClassifierFromSimplifiedTS(Classifier, TimeSeriesDataset2) - Static method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.util.WekaTimeseriesUtil: Trains a given Weka classifier using the simplified time series data set timeSeriesDataset.

C

cacheRetrievals - Static variable in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNode
calculateD(double[][][], int, int, double[], int, int) - Static method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm: Function to calculate the distance between the j-th segment of the given time series instance and the k-th shapelet stored in the shapelet tensor S.
calculateDeltaEntropy(double[], int[], double, List<Integer>, double) - Static method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeLearningAlgorithm: Function calculating the delta entropy for a given thresholdCandidate and parentEntropy.
calculateEntrance(double, double) - Static method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeLearningAlgorithm: Calculates the entrance gain specified by Deng et. al. in the paper's chapter 4.1.
calculateMargin(double[], double) - Static method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeLearningAlgorithm: Function calculating the margin between the given thresholdCandidate and the nearest feature value from the given dataValues.
calculateMHat(double[][][], int, int, double[], int, int, double) - Static method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm: Function to calculate the soft-minimum function which is a differentiable approximation of the minimum distance matrix given in the paper in section 3.1.4.
call() - Method in class ai.libs.jaicore.ml.weka.classification.learner.WekaLearningAlgorithm
call() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm: Main function to train a LearnShapeletsClassifier.
call() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityLearningAlgorithm: Training procedure for a LearnPatternSimilarityClassifier.
call() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesLearningAlgorithm: Training procedure construction a Time Series Bag-of-Features (TSBF) classifier using the given input data.
call() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesForestLearningAlgorithm: Training procedure construction a time series tree using the given input data.
call() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeLearningAlgorithm: Training procedure construction a time series tree using the given input data.
call() - Method in class ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformLearningAlgorithm: Training procedure for ShapeletTransformTSClassifier using the training algorithm described in the paper.
call() - Method in class ai.libs.jaicore.ml.weka.preprocessing.WekaPreprocessorFitter
cancel() - Method in class ai.libs.jaicore.ml.weka.classification.learner.WekaLearningAlgorithm
cancel() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeLearningAlgorithm
cancel() - Method in class ai.libs.jaicore.ml.weka.preprocessing.WekaPreprocessorFitter
CategoricalFeatureDomain - Class in ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace: Description of a categorical feature domain.
CategoricalFeatureDomain(double[]) - Constructor for class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.CategoricalFeatureDomain
CategoricalFeatureDomain(CategoricalFeatureDomain) - Constructor for class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.CategoricalFeatureDomain
center - Variable in class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.Kmeans
ChooseKAugSpaceSampler - Class in ai.libs.jaicore.ml.weka.rangequery: Samples interval-valued data from a dataset of precise points by sampling k precise points (with replacement) and generating a point in the interval-valued augmented space by only considering those k points, i.e. choosing respective minima and maxima for each attribute from the chosen precise points.
ChooseKAugSpaceSampler(Instances, Random, int) - Constructor for class ai.libs.jaicore.ml.weka.rangequery.ChooseKAugSpaceSampler
ClassifierCache - Class in ai.libs.jaicore.ml.weka.classification.learner.reduction
ClassifierCache() - Constructor for class ai.libs.jaicore.ml.weka.classification.learner.reduction.ClassifierCache
ClassifierRankingForGroup - Class in ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac
classifyInstance(Instance) - Method in class ai.libs.jaicore.ml.weka.classification.learner.Ensemble
classifyInstance(Instance) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.AMCTreeNode
classifyInstance(Instance) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.ConstantClassifier
classifyInstance(Instance) - Method in interface ai.libs.jaicore.ml.weka.classification.learner.reduction.ITreeClassifier
classifyInstance(Instance) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeLeaf
classifyInstance(Instance) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeReDLeaf
classifyInstance(Instance) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.reducer.HighProbClassifier
classifyInstance(Instance) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.reducer.ReductionOptimizer
classifyInstance(Instance) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.MLPipeline
classifyInstance(Instance) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.MLSophisticatedPipeline
classifyInstance(Instance) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.ensemble.MajorityConfidenceVote
classifyInstances(Instances) - Method in interface ai.libs.jaicore.ml.weka.classification.IInstancesClassifier
classifyInstances(Instances) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.MLPipeline
clearCache() - Static method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNode
clone() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.ConstantClassifier
cloneClassifier(Classifier) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
Cluster - Class in ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac
clusterDeprecated() - Method in class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.ModifiedISACgMeans
clusterShapelets() - Method in interface ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformLearningAlgorithm.IShapeletTransformLearningAlgorithmConfig: Indicator whether clustering of shapelets should be used.
clusterShapelets(List<Shapelet>, int, long) - Method in class ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformLearningAlgorithm: Clusters the given shapelets into noClusters clusters (cf. algorithm 6 of the original paper).
collectLeafCounts(int[], Instance, AccessibleRandomTree) - Static method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityLearningAlgorithm: Function collecting the leaf counts for the given instance as predicted by regTree.
compactString() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.CategoricalFeatureDomain
compactString() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.FeatureDomain
compactString() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.NumericFeatureDomain
computeDistance(double[], double[]) - Method in class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.L1DistanceMetric
computeDistance(A, B) - Method in interface ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.IDistanceMetric
computeMarginalStandardDeviationForSubsetOfFeatures(Set<Integer>) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedRandomTree: Computes the variance contribution of a subset of features.
computeMarginalVarianceContributionForFeatureSubset(Set<Integer>) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedRandomForest
computeMarginalVarianceContributionForFeatureSubsetNotNormalized(Set<Integer>) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedRandomForest
computeMarginalVarianceContributionForSubsetOfFeatures(Set<Integer>) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedRandomTree: Computes the variance contribution of a subset of features.
computeMarginalVarianceContributionForSubsetOfFeaturesNotNormalized(Set<Integer>) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedRandomTree: Computes the variance contribution of a subset of features without normalizing.
computeTotalVarianceOfSubset(Set<Integer>) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedRandomTree: Computes the total variance of marginal predictions for a given set of features.
ConfidenceIntervalClusteringBasedActiveDyadRanker - Class in ai.libs.jaicore.ml.weka.ranking.dyad.learner.activelearning: A prototypical active dyad ranker based on clustering of pseudo confidence intervals.
ConfidenceIntervalClusteringBasedActiveDyadRanker(PLNetDyadRanker, IDyadRankingPoolProvider, int, int, int, Clusterer) - Constructor for class ai.libs.jaicore.ml.weka.ranking.dyad.learner.activelearning.ConfidenceIntervalClusteringBasedActiveDyadRanker
ConstantClassifier - Class in ai.libs.jaicore.ml.weka.classification.learner.reduction
ConstantClassifier() - Constructor for class ai.libs.jaicore.ml.weka.classification.learner.reduction.ConstantClassifier
contains(Object) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.CategoricalFeatureDomain
contains(Object) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.FeatureDomain: Checks if the domain contains an item.
contains(Object) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.NumericFeatureDomain
containsInstance(double) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.CategoricalFeatureDomain
containsInstance(double) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.FeatureDomain: Checks whether a given weka instance is contained in the feature domain
containsInstance(double) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.NumericFeatureDomain
containsInstance(Instance) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.FeatureSpace
containsPartialInstance(List<Integer>, List<Double>) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.FeatureSpace
createBaseClassifier(String, List<String>) - Static method in class ai.libs.jaicore.ml.weka.classification.learner.WekaClassifier
createCopy() - Method in class ai.libs.jaicore.ml.weka.dataset.WekaInstances
createDatasetFromSchema(ILabeledInstanceSchema) - Static method in class ai.libs.jaicore.ml.weka.dataset.WekaInstancesUtil
createEmptyCopy() - Method in interface ai.libs.jaicore.ml.weka.dataset.IWekaInstances
createEmptyCopy() - Method in class ai.libs.jaicore.ml.weka.dataset.WekaInstances
createPipeline(String, List<String>, String, List<String>, String, List<String>) - Static method in class ai.libs.jaicore.ml.weka.classification.learner.WekaClassifier

D

datasetToWekaInstances(ILabeledDataset<? extends ILabeledInstance>) - Static method in class ai.libs.jaicore.ml.weka.dataset.WekaInstancesUtil
decide(TreeNode<TimeSeriesTreeClassifier.TimeSeriesTreeNodeDecisionFunction>, double[]) - Static method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeClassifier: Function performing the decision on a treeNode given the instance based on the locally stored splitting criterion.
defaultClassifierString() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedM5Forest
defaultClassifierString() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedRandomForest
DIRECT - ai.libs.jaicore.ml.weka.classification.learner.reduction.EMCNodeType
discretizeProbs(int, double[][]) - Static method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesLearningAlgorithm: Function discretizing probabilities into bins.
distributionForInstance(Instance) - Method in class ai.libs.jaicore.ml.weka.classification.learner.Ensemble
distributionForInstance(Instance) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.ConstantClassifier
distributionForInstance(Instance) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNode
distributionForInstance(Instance) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeLeaf
distributionForInstance(Instance) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeReD
distributionForInstance(Instance) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeReDLeaf
distributionForInstance(Instance) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.reducer.HighProbClassifier
distributionForInstance(Instance) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.reducer.ReductionOptimizer
distributionForInstance(Instance) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.MLPipeline
distributionForInstance(Instance) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.MLSophisticatedPipeline
distributionForInstance(Instance) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.ensemble.MajorityConfidenceVote: Function calculating the distribution for a instance by predicting the distributions for each classifier and multiplying the result by the classifier weights.
distributionForInstance(Instance) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.AccessibleRandomTree.AccessibleTree
distributionForInstance(Instance) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.AccessibleRandomTree
distributionForInstance(Instance, double[]) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNode
distributionForInstance(Instance, double[]) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeLeaf

E

EMCNodeType - Enum in ai.libs.jaicore.ml.weka.classification.learner.reduction
Ensemble - Class in ai.libs.jaicore.ml.weka.classification.learner
Ensemble() - Constructor for class ai.libs.jaicore.ml.weka.classification.learner.Ensemble
EnsembleProvider - Class in ai.libs.jaicore.ml.weka.classification.timeseries.learner.ensemble: Class statically providing preconfigured ensembles as commonly used in TSC implementations.
ENTROPY_APLHA - Static variable in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeLearningAlgorithm: Alpha parameter used to weight the importance of the feature's margins to the threshold candidates.
equals(Object) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.SupervisedFilterSelector
equals(Object) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.SuvervisedFilterPreprocessor
equals(Object) - Method in class ai.libs.jaicore.ml.weka.dataset.WekaInstance
equals(Object) - Method in class ai.libs.jaicore.ml.weka.dataset.WekaInstances
equals(Object) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.CategoricalFeatureDomain
equals(Object) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.NumericFeatureDomain
estimateK() - Method in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.ILearnShapeletsLearningAlgorithmConfig: Parameter indicator whether estimation of K (number of learned shapelets) should be derived from the number of total segments.
estimateK() - Method in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm.ILearnShapeletsLearningAlgorithmConfig: Parameter indicator whether estimation of K (number of learned shapelets) should be derived from the number of total segments.
estimateShapeletLengthBorders() - Method in interface ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformLearningAlgorithm.IShapeletTransformLearningAlgorithmConfig: Indicator whether the min max estimation should be performed.
ExactIntervalAugSpaceSampler - Class in ai.libs.jaicore.ml.weka.rangequery: Samples interval-valued data from a dataset of precise points.
ExactIntervalAugSpaceSampler(Instances, Random) - Constructor for class ai.libs.jaicore.ml.weka.rangequery.ExactIntervalAugSpaceSampler
ExtendedM5Forest - Class in ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree
ExtendedM5Forest() - Constructor for class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedM5Forest
ExtendedM5Forest(int) - Constructor for class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedM5Forest
ExtendedM5Forest(IntervalAggregator, IntervalAggregator) - Constructor for class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedM5Forest
ExtendedM5Tree - Class in ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree
ExtendedM5Tree() - Constructor for class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedM5Tree
ExtendedM5Tree(IntervalAggregator) - Constructor for class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedM5Tree
ExtendedRandomForest - Class in ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree
ExtendedRandomForest() - Constructor for class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedRandomForest
ExtendedRandomForest(int) - Constructor for class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedRandomForest
ExtendedRandomForest(IntervalAggregator, IntervalAggregator) - Constructor for class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedRandomForest
ExtendedRandomForest(IntervalAggregator, IntervalAggregator, FeatureSpace) - Constructor for class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedRandomForest
ExtendedRandomForest(FeatureSpace) - Constructor for class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedRandomForest
ExtendedRandomTree - Class in ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree: Extension of a classic RandomTree to predict intervals.
ExtendedRandomTree() - Constructor for class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedRandomTree
ExtendedRandomTree(IntervalAggregator) - Constructor for class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedRandomTree
ExtendedRandomTree(FeatureSpace) - Constructor for class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedRandomTree
extractSchema(Instances) - Static method in class ai.libs.jaicore.ml.weka.dataset.WekaInstancesUtil

F

FeatureDomain - Class in ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace: Abstract description of a feature domain.
FeatureDomain() - Constructor for class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.FeatureDomain
FeatureGenerator - Interface in ai.libs.jaicore.ml.weka.classification.pipeline.featuregen
FeatureGeneratorTree - Class in ai.libs.jaicore.ml.weka.classification.pipeline.featuregen
FeatureGeneratorTree(FeatureGenerator) - Constructor for class ai.libs.jaicore.ml.weka.classification.pipeline.featuregen.FeatureGeneratorTree
FeaturePreprocessor - Interface in ai.libs.jaicore.ml.weka.classification.pipeline
FeatureSpace - Class in ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace
FeatureSpace() - Constructor for class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.FeatureSpace
FeatureSpace(FeatureDomain[]) - Constructor for class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.FeatureSpace
FeatureSpace(FeatureSpace) - Constructor for class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.FeatureSpace
FeatureSpace(List<FeatureDomain>) - Constructor for class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.FeatureSpace: copy constructor
FeatureSpace(Instances) - Constructor for class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.FeatureSpace
findDistances(Shapelet, double[][]) - Method in class ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformLearningAlgorithm: Function finding the minimum single squared Euclidean distance for each instance among all of its subsequences compared to the shapelet s.
findNearestInstanceIndex(int[][]) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityClassifier: Performs a simple nearest neighbor search on the stored trainLeafNodes for the given leafNodeCounts using Manhattan distance.
fit(ILabeledDataset<? extends ILabeledInstance>) - Method in class ai.libs.jaicore.ml.weka.classification.learner.AWekaLearner
fit(ILabelRankingDataset) - Method in class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.ModifiedISAC
fit(Instances, int) - Method in class ai.libs.jaicore.ml.weka.RankingByPairwiseComparison
formHistogramsAndRelativeFreqs(int[][], int, int, int) - Static method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesLearningAlgorithm: Function calculating the histograms as described in the paper's section 2.2 ("Codebook and Learning").

G

gamma() - Method in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.ILearnShapeletsLearningAlgorithmConfig: Gamma value used for momentum during gradient descent.
gamma() - Method in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm.ILearnShapeletsLearningAlgorithmConfig: Gamma value used for momentum during gradient descent.
generateAugPoint(List<Instance>) - Static method in class ai.libs.jaicore.ml.weka.rangequery.AbstractAugmentedSpaceSampler
generateCandidates(double[], int, int) - Static method in class ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformLearningAlgorithm: Function generation shapelet candidates for a given instance vector data, the length l and the candidate index which is used to identify the source of the shapelet's data.
generateFeatures(double[][], int[][], int[][][]) - Static method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesLearningAlgorithm: Function generating the features for the internal probability measurement model based on the given subseries and their corresponding intervals.
generateHistogramInstances(int[][][], int[][]) - Static method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesLearningAlgorithm: Generates a matrix consisting of the histogram values for each instance out of the given histograms and the relative frequencies of classes for each instance.
generateSegmentsAndDifferencesForTree(int[], int[], int, int, Random) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityLearningAlgorithm: Method generating the segment start indices and the segment difference locations randomly using random.
generateSubsequencesAndIntervals(int, int, int, int) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesLearningAlgorithm: Method randomly determining the subsequences and their intervals to be used for feature generation of the instances.
generateSubseriesFeatureInstance(double[], int[], int[], int) - Static method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityLearningAlgorithm: Function generating subseries feature instances based on the given segments and segmentsDifference matrices.
generateSubseriesFeaturesInstances(List<Attribute>, int, int[], int[], double[][]) - Static method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityLearningAlgorithm: Function generating a dataset storing the features being generated as described in the original paper.
generateThresholdCandidates(Pair<List<Integer>, List<Integer>>, int, double[][][]) - Static method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeLearningAlgorithm: Function generating threshold candidates for each feature type.
getAdmissibleSearcherEvaluatorCombinationsForAttributeSelection() - Static method in class ai.libs.jaicore.ml.weka.WekaUtil: Determines all attribute selection variants (search/evaluator combinations with default parametrization)
getAllClassifier() - Method in class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.ModifiedISACInstanceCollector
getArbitrarySplit(IWekaInstances, Random, double...) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getAtributesofTrainingsdata() - Static method in class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.ModifiedISACInstanceCollector
getAttribute() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.AccessibleRandomTree.AccessibleTree
getAttributes() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityClassifier
getAttributes() - Method in class ai.libs.jaicore.ml.weka.dataset.WekaInstance
getAttributes(Instance) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getAttributes(Instances, boolean) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getAttributeValue(int) - Method in class ai.libs.jaicore.ml.weka.dataset.WekaInstance
getAverageSeparability(Collection<String>) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.AllPairsTable
getBaseClassifier() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.MLPipeline
getBaseClassifier() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.MLSophisticatedPipeline
getBaseLearner() - Method in interface ai.libs.jaicore.ml.weka.RPCConfig
getBasicClassifiers() - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getBasicLearners() - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getBestSplitIndex(double[]) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeLearningAlgorithm: Function returning feature type used for the split based on given the deltaEntropy star values.
getBinaryClassifiers() - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getC() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm
getCachedClassifier(String, EMCNodeType, Instances) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.ClassifierCache
getCachedTrainingData(String, EMCNodeType, Instances) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.ClassifierCache
getCapabilities() - Method in class ai.libs.jaicore.ml.weka.classification.learner.Ensemble
getCapabilities() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.ConstantClassifier
getCapabilities() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNode
getCapabilities() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeLeaf
getCapabilities() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeReD
getCapabilities() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeReDLeaf
getCapabilities() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.reducer.HighProbClassifier
getCapabilities() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.reducer.ReductionOptimizer
getCapabilities() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.MLPipeline
getCapabilities() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.MLSophisticatedPipeline
getCenter() - Method in class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.ModifiedISACkMeans
getChildDataIndices(double[][][], int, int, int, double) - Static method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeLearningAlgorithm: Function returning the data indices assigned to the left and the right child of a binary tree based on the splitting criterion given by the feature type fType, the intervals index t1t2 in the transformed data set transformedData and the threshold.
getChildren() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNode
getChildren() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeReD
getClassAttIndexPerTree() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityClassifier
getClassesActuallyContainedInDataset(Instances) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getClassesAsArray(Instances) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getClassesAsList(Instances) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getClassesDeclaredInDataset(Instances) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getClassifier() - Method in class ai.libs.jaicore.ml.weka.classification.learner.AWekaLearner
getClassifier() - Method in interface ai.libs.jaicore.ml.weka.classification.learner.IWekaClassifier
getClassifier() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNode
getClassifier() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeReD
getClassifierCache() - Static method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNode
getClassifierDescriptor(Classifier) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getClassName(Instance) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getClassNames(Instance) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getClassNameToIDMap(Instance) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getClassSplitAssignments(List<Instances>) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getCollectedClassifierandPerformance() - Method in class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.ModifiedISACInstanceCollector
getConfig() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm
getConfig() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityLearningAlgorithm
getConfig() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesClassifier
getConfig() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesLearningAlgorithm
getConfig() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesForestLearningAlgorithm
getConfig() - Method in class ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformLearningAlgorithm
getConstructionPlan() - Method in class ai.libs.jaicore.ml.weka.classification.learner.AWekaLearner
getConstructionPlan() - Method in class ai.libs.jaicore.ml.weka.dataset.WekaInstances
getConstructorForDecoratingItems() - Method in class ai.libs.jaicore.ml.weka.dataset.WekaInstances
getContainedClasses() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.AMCTreeNode
getContainedClasses() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeReD
getCurrentPoints() - Method in class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.ModifiedISACgMeans
getDatasetsInFolder(File) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getDepthOfFirstCommonParent(List<Integer>) - Method in interface ai.libs.jaicore.ml.weka.classification.learner.reduction.ITreeClassifier
getDepthOfFirstCommonParent(List<Integer>) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNode
getDepthOfFirstCommonParent(List<String>) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeReD
getDescriptor(Object) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getDimensionality() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.FeatureSpace
getElement() - Method in interface ai.libs.jaicore.ml.weka.dataset.IWekaInstance
getEmptySetOfInstancesWithRefactoredClass(Instances) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getEmptySetOfInstancesWithRefactoredClass(Instances, List<String>) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getEntry(Interval[], T) - Static method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.util.RQPHelper
getEvaluator() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.SupervisedFilterSelector
getEvaluator() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.SuvervisedFilterPreprocessor
getFeatureDomain(int) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.FeatureSpace
getFeatureDomains() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.FeatureSpace
getFeatureEvaluators() - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getFeatureMatrix() - Method in class ai.libs.jaicore.ml.weka.dataset.WekaInstances
getFeatureSpace() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedRandomForest
getFeatureSpace() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedRandomTree
getFinalClf() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesClassifier
getFrequency(IWekaInstance) - Method in class ai.libs.jaicore.ml.weka.dataset.WekaInstances
getHeaderInformation() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.util.RQPHelper.IntervalAndHeader
getHeight() - Method in interface ai.libs.jaicore.ml.weka.classification.learner.reduction.ITreeClassifier
getHeight() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNode
getHeight() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeLeaf
getHeight() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeReD
getHeight() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeReDLeaf
getIndicesOfContainedInstances(Instances, Instances) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil: Compute indices of instances of the original data set that are contained in the given subset.
getIndicesOfSubset(Instances, Instances) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getInstances() - Method in interface ai.libs.jaicore.ml.weka.dataset.IWekaInstances
getInstances() - Method in class ai.libs.jaicore.ml.weka.dataset.WekaInstances
getInstanceSchema() - Method in class ai.libs.jaicore.ml.weka.dataset.WekaInstances
getInstancesOfClass(Instances, String) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getInstancesOfClass(Instances, Collection<String>) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getInstancesPerClass(Instances) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getIntermediateCenter() - Method in class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.ModifiedISACgMeans
getIntermediatePoints() - Method in class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.ModifiedISACgMeans
getIntervals() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesClassifier
getIntervals() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.util.RQPHelper.IntervalAndHeader
getIntValOfClassName(Instance, String) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getK() - Method in class ai.libs.jaicore.ml.weka.rangequery.ChooseKAugSpaceSampler
getK() - Method in class ai.libs.jaicore.ml.weka.rangequery.KNNAugSpaceSampler
getLabel() - Method in class ai.libs.jaicore.ml.weka.dataset.WekaInstance
getLabelVector() - Method in class ai.libs.jaicore.ml.weka.dataset.WekaInstances
getLastNode() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.AccessibleRandomTree
getLearningAlgorithm(TimeSeriesDataset2) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsClassifier
getLearningAlgorithm(TimeSeriesDataset2) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityClassifier
getLearningAlgorithm(TimeSeriesDataset2) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesClassifier
getLearningAlgorithm(TimeSeriesDataset2) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesForestClassifier
getLearningAlgorithm(TimeSeriesDataset2) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeClassifier
getLearningAlgorithm(TimeSeriesDataset2) - Method in class ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformTSClassifier
getLengthPerTree() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityClassifier
getList() - Method in interface ai.libs.jaicore.ml.weka.dataset.IWekaInstances
getList() - Method in class ai.libs.jaicore.ml.weka.dataset.WekaInstances
getLoopPoints() - Method in class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.ModifiedISACgMeans
getMax() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.NumericFeatureDomain
getMetaLearners() - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getMin() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.NumericFeatureDomain
getMinDistanceSearchStrategy() - Method in class ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformLearningAlgorithm: Getter for ShapeletTransformLearningAlgorithm.minDistanceSearchStrategy.
getMinDistanceSearchStrategy() - Method in class ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformTSClassifier: Getter for ShapeletTransformTSClassifier.minDistanceSearchStrategy.
getMTree() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.AccessibleRandomTree
getMultipliedSeparability(Collection<String>) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.AllPairsTable
getName() - Method in class ai.libs.jaicore.ml.weka.classification.learner.AWekaLearner
getName() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.FeatureDomain: Getter for name attribute.
getNativeMultiClassClassifiers() - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getNewClassAttribute(Attribute) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getNewClassAttribute(Attribute, List<String>) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getNodeType() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNode
getNosLeafNodes() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.AccessibleRandomTree
getNumberOfClassifier() - Method in class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.ModifiedISACInstanceCollector
getNumberOfInstancesFromClass(Instances, String) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getNumberOfInstancesFromClass(Instances, Collection<String>) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getNumberOfInstancesPerClass(Instances) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getNumberOfSegments(int, int, int) - Static method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm: Returns the number of segments which are available for a instance with Q attributes for a given scale r and a minimum shape length minShapeLength.
getNumBins() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesClassifier
getNumClasses() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesClassifier
getNumCPUs() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeLearningAlgorithm
getOptions() - Method in class ai.libs.jaicore.ml.weka.classification.learner.AWekaLearner
getOptions() - Method in interface ai.libs.jaicore.ml.weka.classification.learner.IWekaClassifierConfig
getOptionsAsList() - Method in class ai.libs.jaicore.ml.weka.classification.learner.AWekaLearner
getOptionsOfWekaAlgorithm(Object) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getPoint() - Method in class ai.libs.jaicore.ml.weka.dataset.WekaInstance
getPointToInstance() - Method in class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.ModifiedISACgMeans
getPointValue(int) - Method in class ai.libs.jaicore.ml.weka.dataset.WekaInstance
getPossibleClassValues(Instance) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getPotence() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.featuregen.PolynomialFeatures
getPreciseInsts() - Method in class ai.libs.jaicore.ml.weka.rangequery.AbstractAugmentedSpaceSampler
getPredictionListAsBatch(List<ISingleLabelClassification>) - Method in class ai.libs.jaicore.ml.weka.classification.learner.WekaClassifier
getPredictionListAsBatch(List<IRegressionPrediction>) - Method in class ai.libs.jaicore.ml.weka.regression.learner.WekaRegressor
getPredictionListAsBatch(List<P>) - Method in class ai.libs.jaicore.ml.weka.classification.learner.AWekaLearner
getPreprocessorDescriptor(ASEvaluation) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getPreprocessorDescriptor(ASSearch) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getPreprocessors() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.MLPipeline
getProblemInstances() - Method in class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.ModifiedISACInstanceCollector
getRangeSize() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.CategoricalFeatureDomain
getRangeSize() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.FeatureDomain: Computes the size of the domain.
getRangeSize() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.FeatureSpace
getRangeSize() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.NumericFeatureDomain
getRangeSizeOfAllButSubset(Set<Integer>) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.FeatureSpace
getRangeSizeOfFeatureSubspace(Set<Integer>) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.FeatureSpace
getRanking(ILabelRankingInstance) - Method in class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.ModifiedISAC
getRankings() - Method in class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.ModifiedISAC
getRefactoredInstance(Instance) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getRefactoredInstance(Instance, List<String>) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getRefactoredInstances(Instances, Map<String, String>) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getRelativeNumberOfInstancesFromClass(Instances, String) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getRelativeNumberOfInstancesFromClass(Instances, Collection<String>) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getReplacedAttributeList(List<Attribute>, Attribute) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getRng() - Method in class ai.libs.jaicore.ml.weka.rangequery.AbstractAugmentedSpaceSampler
getRoot() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.featuregen.FeatureGeneratorTree
getRootGenerator() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.reducer.ReductionGraphGenerator
getRootNode() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeClassifier: Getter for the root node.
getS() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsClassifier
getSearcher() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.SupervisedFilterSelector
getSearcher() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.SuvervisedFilterPreprocessor
getSearchers() - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getSegments() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityClassifier
getSegmentsDifference() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityClassifier
getSelector() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.SupervisedFilterSelector
getSelector() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.SuvervisedFilterPreprocessor
getSelector() - Method in class ai.libs.jaicore.ml.weka.preprocessing.WekaPreprocessorFitter
getSeparability(String, String) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.AllPairsTable
getShapelets() - Method in class ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformTSClassifier: Getter for ShapeletTransformTSClassifier.shapelets.
getSize() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedRandomForest
getSplitPoint() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.AccessibleRandomTree.AccessibleTree
getSplitter(int) - Method in interface ai.libs.jaicore.ml.weka.classification.learner.reduction.splitter.ISplitterFactory
getStratifiedSplit(IWekaInstances, long, double) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getStratifiedSplit(IWekaInstances, Random, double) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getStratifiedSplit(Instances, long, double) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
getSubsequences() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesClassifier
getSubseriesClf() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesClassifier
getSuccessorGenerator() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.reducer.ReductionGraphGenerator
getSuccessors() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.AccessibleRandomTree.AccessibleTree
getTimeForExecutingClassifier() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.MLPipeline
getTimeForExecutingClassifier() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.MLSophisticatedPipeline
getTimeForExecutingPreprocessor() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.MLPipeline
getTimeForExecutingPreprocessor() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.MLSophisticatedPipeline
getTimeForTrainingClassifier() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.MLPipeline
getTimeForTrainingClassifier() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.MLSophisticatedPipeline
getTimeForTrainingPreprocessor() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.MLPipeline
getTimeForTrainingPreprocessor() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.MLSophisticatedPipeline
getTimeout() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeLearningAlgorithm
getTotalVariance() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedRandomTree
getTrainLeafNodes() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityClassifier
getTrainTargets() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityClassifier
getTrees() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityClassifier
getTrees() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesForestClassifier: Getter for the time series trees.
getTypeOfDecoratedItems() - Method in class ai.libs.jaicore.ml.weka.dataset.WekaInstances
getTypeOfDecoratingItems() - Method in class ai.libs.jaicore.ml.weka.dataset.WekaInstances
getUpperBoundOnSeparability(Collection<String>) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.AllPairsTable
getValues() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.CategoricalFeatureDomain
getVotingStrategy() - Method in interface ai.libs.jaicore.ml.weka.RPCConfig
getW() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsClassifier
getW0() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsClassifier
getWekaInstance(ILabeledInstance) - Method in class ai.libs.jaicore.ml.weka.classification.learner.AWekaLearner

H

hashCode() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.SupervisedFilterSelector
hashCode() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.SuvervisedFilterPreprocessor
hashCode() - Method in class ai.libs.jaicore.ml.weka.dataset.WekaInstance
hashCode() - Method in class ai.libs.jaicore.ml.weka.dataset.WekaInstances
hashCode() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.CategoricalFeatureDomain
hashCode() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.NumericFeatureDomain
hasNext() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeLearningAlgorithm
hasOnlyNumericAttributes(Instances) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
HighProbClassifier - Class in ai.libs.jaicore.ml.weka.classification.learner.reduction.reducer
HighProbClassifier(Classifier) - Constructor for class ai.libs.jaicore.ml.weka.classification.learner.reduction.reducer.HighProbClassifier

I

IAugmentedSpaceSampler - Interface in ai.libs.jaicore.ml.weka.rangequery: Interface representing a class that samples interval-valued data from a set of precise data points.
IAugSpaceSamplingFunction - Interface in ai.libs.jaicore.ml.weka.rangequery
IDistanceMetric<D,A,B> - Interface in ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac
IInstancesClassifier - Interface in ai.libs.jaicore.ml.weka.classification
ILearnShapeletsLearningAlgorithmConfig - Interface in ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets
initializeKMeans() - Method in class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.Kmeans
initializeKMeans() - Method in class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.ModifiedISACkMeans
initializeRegressionTree(int) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityLearningAlgorithm: Initializes a new instance of RandomRegressionTree.
initializeS(double[][]) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm: Initializes the tensor S storing the shapelets for each scale.
initializeWeights(double[][][], double[]) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm: Randomly initializes the weights around zero.
instances2matrix(Instances) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil: Binarizes nominal features and returns an ND4J matrix
instancesToJsonString(Instances) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
InteractingFeatures - Class in ai.libs.jaicore.ml.weka.classification.pipeline.featuregen
InteractingFeatures() - Constructor for class ai.libs.jaicore.ml.weka.classification.pipeline.featuregen.InteractingFeatures
IntervalAggregator - Interface in ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.aggregation: An IntervalAggeregator can aggregate from a list of intervals, more precisely given a list of predictions in the leaf node, it can predict a range.
IntervalAndHeader(Interval[], Instances) - Constructor for class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.util.RQPHelper.IntervalAndHeader
isCompletelyConfigured() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNode
isCompletelyConfigured() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeLeaf
isCompletelyConfigured() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeReD
isCompletelyConfigured() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeReDLeaf
isDebug() - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
isInteger() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.NumericFeatureDomain
ISplitter - Interface in ai.libs.jaicore.ml.weka.classification.learner.reduction.splitter
ISplitterFactory<T extends ISplitter> - Interface in ai.libs.jaicore.ml.weka.classification.learner.reduction.splitter
isPrepared() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.featuregen.FeatureGeneratorTree
isPrepared() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.featuregen.InteractingFeatures
isPrepared() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.featuregen.PolynomialFeatures
isPrepared() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.featurepreprocess.Normalization
isPrepared() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.featurepreprocess.Standardization
isPrepared() - Method in interface ai.libs.jaicore.ml.weka.classification.pipeline.FeaturePreprocessor
isPrepared() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.MLSophisticatedPipeline
isPrepared() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.SupervisedFilterSelector
isPrepared() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.SuvervisedFilterPreprocessor
isUseInstanceReordering() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm
isValidPreprocessorCombination(String, String) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
iterator() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNode
iterator() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeLearningAlgorithm
ITreeClassifier - Interface in ai.libs.jaicore.ml.weka.classification.learner.reduction
IWekaClassifier - Interface in ai.libs.jaicore.ml.weka.classification.learner
IWekaClassifierConfig - Interface in ai.libs.jaicore.ml.weka.classification.learner
IWekaInstance - Interface in ai.libs.jaicore.ml.weka.dataset
IWekaInstances - Interface in ai.libs.jaicore.ml.weka.dataset
IWekaLearningAlgorithm - Interface in ai.libs.jaicore.ml.weka.classification.learner
IWekaPreprocessingAlgorithm - Interface in ai.libs.jaicore.ml.weka.preprocessing: A WEKA preprocessing algorithm takes a labeled dataset and produces itself as to allow for applying the obtained dimensionality reduction to some new data.

J

jsonStringToInstances(String) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil

K

k - Variable in class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.Kmeans
K_BASE_LEARNER - Static variable in interface ai.libs.jaicore.ml.weka.RPCConfig
K_CLUSTERSHAPELETS - Static variable in interface ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformLearningAlgorithm.IShapeletTransformLearningAlgorithmConfig
K_ESTIMATEK - Static variable in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.ILearnShapeletsLearningAlgorithmConfig
K_ESTIMATEK - Static variable in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm.ILearnShapeletsLearningAlgorithmConfig
K_ESTIMATESHAPELETLENGTHBORDERS - Static variable in interface ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformLearningAlgorithm.IShapeletTransformLearningAlgorithmConfig
K_FEATURECACHING - Static variable in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesForestLearningAlgorithm.ITimeSeriesForestConfig
K_FEATURECACHING - Static variable in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeLearningAlgorithm.ITimeSeriesTreeConfig
K_GAMMA - Static variable in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.ILearnShapeletsLearningAlgorithmConfig
K_GAMMA - Static variable in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm.ILearnShapeletsLearningAlgorithmConfig
K_LEARNINGRATE - Static variable in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.ILearnShapeletsLearningAlgorithmConfig
K_LEARNINGRATE - Static variable in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm.ILearnShapeletsLearningAlgorithmConfig
K_MAXDEPTH - Static variable in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityLearningAlgorithm.IPatternSimilarityConfig
K_MAXDEPTH - Static variable in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesForestLearningAlgorithm.ITimeSeriesForestConfig
K_MAXDEPTH - Static variable in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeLearningAlgorithm.ITimeSeriesTreeConfig
K_MAXITER - Static variable in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.ILearnShapeletsLearningAlgorithmConfig
K_MAXITER - Static variable in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm.ILearnShapeletsLearningAlgorithmConfig
K_MIN_INTERVAL_LENGTH - Static variable in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesLearningAlgorithm.ITimeSeriesBagOfFeaturesConfig
K_NUM_SHAPELETS - Static variable in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.ILearnShapeletsLearningAlgorithmConfig
K_NUMBINS - Static variable in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesLearningAlgorithm.ITimeSeriesBagOfFeaturesConfig
K_NUMCLUSTERS - Static variable in interface ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformLearningAlgorithm.IShapeletTransformLearningAlgorithmConfig
K_NUMFOLDS - Static variable in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesLearningAlgorithm.ITimeSeriesBagOfFeaturesConfig
K_NUMFOLDS - Static variable in interface ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformLearningAlgorithm.IShapeletTransformLearningAlgorithmConfig
K_NUMSEGMENTS - Static variable in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityLearningAlgorithm.IPatternSimilarityConfig
K_NUMSHAPELETS - Static variable in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm.ILearnShapeletsLearningAlgorithmConfig
K_NUMSHAPELETS - Static variable in interface ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformLearningAlgorithm.IShapeletTransformLearningAlgorithmConfig
K_NUMTREES - Static variable in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityLearningAlgorithm.IPatternSimilarityConfig
K_NUMTREES - Static variable in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesForestLearningAlgorithm.ITimeSeriesForestConfig
K_REGULARIZATION - Static variable in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.ILearnShapeletsLearningAlgorithmConfig
K_REGULARIZATION - Static variable in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm.ILearnShapeletsLearningAlgorithmConfig
K_SCALER - Static variable in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.ILearnShapeletsLearningAlgorithmConfig
K_SCALER - Static variable in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm.ILearnShapeletsLearningAlgorithmConfig
K_SHAPELETLENGTH_MAX - Static variable in interface ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformLearningAlgorithm.IShapeletTransformLearningAlgorithmConfig
K_SHAPELETLENGTH_MIN - Static variable in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.ILearnShapeletsLearningAlgorithmConfig
K_SHAPELETLENGTH_MIN - Static variable in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm.ILearnShapeletsLearningAlgorithmConfig
K_SHAPELETLENGTH_MIN - Static variable in interface ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformLearningAlgorithm.IShapeletTransformLearningAlgorithmConfig
K_SHAPELETLENGTH_RELMIN - Static variable in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.ILearnShapeletsLearningAlgorithmConfig
K_SHAPELETLENGTH_RELMIN - Static variable in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm.ILearnShapeletsLearningAlgorithmConfig
K_USE_ZNORMALIZATION - Static variable in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesLearningAlgorithm.ITimeSeriesBagOfFeaturesConfig
K_USEHIVECOTEENSEMBLE - Static variable in interface ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformLearningAlgorithm.IShapeletTransformLearningAlgorithmConfig
K_VOTING_STRATEGY - Static variable in interface ai.libs.jaicore.ml.weka.RPCConfig
K_ZPROP - Static variable in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesLearningAlgorithm.ITimeSeriesBagOfFeaturesConfig
Kmeans<A,D> - Class in ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac
Kmeans(List<A>, IDistanceMetric<D, A, A>) - Constructor for class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.Kmeans
kmeanscluster(int) - Method in class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.Kmeans
kmeanscluster(int) - Method in class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.ModifiedISACkMeans
KNNAugSpaceSampler - Class in ai.libs.jaicore.ml.weka.rangequery: Samples interval-valued data from a dataset of precise points.
KNNAugSpaceSampler(Instances, Random, int, NearestNeighbourSearch) - Constructor for class ai.libs.jaicore.ml.weka.rangequery.KNNAugSpaceSampler

L

L1DistanceMetric - Class in ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac
L1DistanceMetric() - Constructor for class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.L1DistanceMetric
learningRate() - Method in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.ILearnShapeletsLearningAlgorithmConfig: The learning rate used within the SGD.
learningRate() - Method in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm.ILearnShapeletsLearningAlgorithmConfig: The learning rate used within the SGD.
LearnPatternSimilarityClassifier - Class in ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees: Class representing the Learn Pattern Similarity classifier as described in Baydogan, Mustafa & Runger, George. (2015).
LearnPatternSimilarityClassifier(int, int, int, int) - Constructor for class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityClassifier: Standard constructor.
LearnPatternSimilarityLearningAlgorithm - Class in ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees: Algorithm training a LearnPatternSimilarityClassifier as described in Baydogan, Mustafa & Runger, George. (2015).
LearnPatternSimilarityLearningAlgorithm(LearnPatternSimilarityLearningAlgorithm.IPatternSimilarityConfig, LearnPatternSimilarityClassifier, TimeSeriesDataset2) - Constructor for class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityLearningAlgorithm: Standard constructor.
LearnPatternSimilarityLearningAlgorithm.IPatternSimilarityConfig - Interface in ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees
LearnShapeletsClassifier - Class in ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets: LearnShapeletsClassifier published in "J.
LearnShapeletsClassifier(int, double, double, int, double, int, double, int) - Constructor for class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsClassifier: Constructor of the LearnShapeletsClassifier.
LearnShapeletsClassifier(int, double, double, int, double, int, int) - Constructor for class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsClassifier: Constructor of the LearnShapeletsClassifier.
LearnShapeletsLearningAlgorithm - Class in ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets: Generalized Shapelets Learning implementation for LearnShapeletsClassifier published in "J.
LearnShapeletsLearningAlgorithm(LearnShapeletsLearningAlgorithm.ILearnShapeletsLearningAlgorithmConfig, LearnShapeletsClassifier, TimeSeriesDataset2) - Constructor for class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm: Constructor of the algorithm to train a LearnShapeletsClassifier.
LearnShapeletsLearningAlgorithm.ILearnShapeletsLearningAlgorithmConfig - Interface in ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets

M

MajorityConfidenceVote - Class in ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.ensemble: Vote implementation for majority confidence.
MajorityConfidenceVote(int, long) - Constructor for class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.ensemble.MajorityConfidenceVote: Constructor for a majority confidence vote ensemble classifier.
mapJ48InputsToWekaOptions(double, double) - Static method in class ai.libs.jaicore.ml.weka.ranking.dyad.learner.zeroshot.util.ZeroShotUtil
mapMLPInputsToWekaOptions(double, double, double) - Static method in class ai.libs.jaicore.ml.weka.ranking.dyad.learner.zeroshot.util.ZeroShotUtil
mapRFInputsToWekaOptions(double, double, double, double, double) - Static method in class ai.libs.jaicore.ml.weka.ranking.dyad.learner.zeroshot.util.ZeroShotUtil
mapSMORBFInputsToWekaOptions(double, double) - Static method in class ai.libs.jaicore.ml.weka.ranking.dyad.learner.zeroshot.util.ZeroShotUtil
mapWEKAToTree(Instance) - Static method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.util.RQPHelper: Maps the WEKA query to a tree-friendly query while also preserving the header information of the query, this is important for M5 trees.
matrixToWekaInstances(double[][]) - Static method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.util.WekaTimeseriesUtil: Converts a double[][] matrix (number of instances x number of attributes) to Weka instances without any class attribute.
maxDepth() - Method in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityLearningAlgorithm.IPatternSimilarityConfig: Maximum depth of the trained trees.
maxDepth() - Method in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesForestLearningAlgorithm.ITimeSeriesForestConfig: Maximum depth of the trained trees.
maxDepth() - Method in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeLearningAlgorithm.ITimeSeriesTreeConfig
maxIterations() - Method in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.ILearnShapeletsLearningAlgorithmConfig: The maximum iterations used for the SGD.
maxIterations() - Method in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm.ILearnShapeletsLearningAlgorithmConfig: The maximum iterations used for the SGD.
maxShapeletLength() - Method in interface ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformLearningAlgorithm.IShapeletTransformLearningAlgorithmConfig: The maximum length of shapelets to be considered.
MCTreeMergeNode - Class in ai.libs.jaicore.ml.weka.classification.learner.reduction
MCTreeMergeNode(String, Collection<String>, Classifier, Collection<String>, Classifier) - Constructor for class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeMergeNode
MCTreeMergeNode(Classifier, List<Collection<String>>, List<Classifier>) - Constructor for class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeMergeNode
MCTreeNode - Class in ai.libs.jaicore.ml.weka.classification.learner.reduction
MCTreeNode(List<Integer>) - Constructor for class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNode
MCTreeNode(List<Integer>, EMCNodeType, String) - Constructor for class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNode
MCTreeNode(List<Integer>, EMCNodeType, Classifier) - Constructor for class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNode
MCTreeNodeLeaf - Class in ai.libs.jaicore.ml.weka.classification.learner.reduction
MCTreeNodeLeaf(int) - Constructor for class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeLeaf
MCTreeNodeReD - Class in ai.libs.jaicore.ml.weka.classification.learner.reduction
MCTreeNodeReD() - Constructor for class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeReD
MCTreeNodeReD(MCTreeNodeReD) - Constructor for class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeReD
MCTreeNodeReD(String, Collection<String>, String, Collection<String>, String) - Constructor for class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeReD
MCTreeNodeReD(String, Collection<String>, Classifier, Collection<String>, Classifier) - Constructor for class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeReD
MCTreeNodeReD(Classifier, Collection<String>, Classifier, Collection<String>, Classifier) - Constructor for class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeReD
MCTreeNodeReD(Classifier, List<Collection<String>>, List<Classifier>) - Constructor for class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeReD
MCTreeNodeReDLeaf - Class in ai.libs.jaicore.ml.weka.classification.learner.reduction
MCTreeNodeReDLeaf(String) - Constructor for class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeReDLeaf
measureOOBProbabilitiesUsingCV(double[][], int[], int, int, int, RandomForest) - Static method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesLearningAlgorithm: Function measuring the out-of-bag (OOB) probabilities using a cross validation with numFolds many folds.
merge(int, List<Map.Entry<Shapelet, Double>>, List<Map.Entry<Shapelet, Double>>) - Static method in class ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformLearningAlgorithm: Function merging shapelet lists based on their quality scores.
merge(Collection<Instances>) - Method in class ai.libs.jaicore.ml.weka.WekaInstancesFeatureUnion
merge(Instances, Instances) - Method in class ai.libs.jaicore.ml.weka.WekaInstancesFeatureUnion
MERGE - ai.libs.jaicore.ml.weka.classification.learner.reduction.EMCNodeType
mergeClassesOfInstances(Instances, Collection<String>, Collection<String>) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
mergeClassesOfInstances(Instances, List<Set<String>>) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
metric - Variable in class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.Kmeans
minIntervalLength() - Method in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesLearningAlgorithm.ITimeSeriesBagOfFeaturesConfig: The minimal interval length used for the interval generation.
minShapeLengthPercentage() - Method in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.ILearnShapeletsLearningAlgorithmConfig: The minimum shape length percentage used to calculate the minimum shape length.
minShapeLengthPercentage() - Method in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm.ILearnShapeletsLearningAlgorithmConfig: The minimum shape length percentage used to calculate the minimum shape length.
minShapeletLength() - Method in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.ILearnShapeletsLearningAlgorithmConfig: The minimum shapelet of the shapelets to be learned.
minShapeletLength() - Method in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm.ILearnShapeletsLearningAlgorithmConfig: The minimum shapelet of the shapelets to be learned.
minShapeletLength() - Method in interface ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformLearningAlgorithm.IShapeletTransformLearningAlgorithmConfig: The minimum length of shapelets to be considered.
MLPipeline - Class in ai.libs.jaicore.ml.weka.classification.pipeline
MLPipeline(List<SupervisedFilterSelector>, Classifier) - Constructor for class ai.libs.jaicore.ml.weka.classification.pipeline.MLPipeline
MLPipeline(ASSearch, ASEvaluation, Classifier) - Constructor for class ai.libs.jaicore.ml.weka.classification.pipeline.MLPipeline
MLSophisticatedPipeline - Class in ai.libs.jaicore.ml.weka.classification.pipeline
MLSophisticatedPipeline(List<FeatureGenerator>, List<FeaturePreprocessor>, List<FeaturePreprocessor>, Classifier) - Constructor for class ai.libs.jaicore.ml.weka.classification.pipeline.MLSophisticatedPipeline
ModifiedISAC - Class in ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac
ModifiedISAC() - Constructor for class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.ModifiedISAC
ModifiedISACgMeans - Class in ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac
ModifiedISACgMeans(List<double[]>, List<ProblemInstance<Instance>>) - Constructor for class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.ModifiedISACgMeans: inilizes toClusterPoints with the points that are to Cluster and are normalized metafeatures
ModifiedISACGroupBuilder - Class in ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac
ModifiedISACGroupBuilder() - Constructor for class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.ModifiedISACGroupBuilder
ModifiedISACInstanceCollector - Class in ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac
ModifiedISACInstanceCollector() - Constructor for class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.ModifiedISACInstanceCollector: This constructor is used if the default file should be used.
ModifiedISACInstanceCollector(Instances, int, int) - Constructor for class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.ModifiedISACInstanceCollector
ModifiedISACkMeans - Class in ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac
ModifiedISACkMeans(List<double[]>, IDistanceMetric<Double, double[], double[]>) - Constructor for class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.ModifiedISACkMeans

N

name - Variable in class ai.libs.jaicore.ml.weka.classification.learner.AWekaLearner
needsBinarization(Instances, boolean) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil: Returns true if there is at least one nominal attribute in the given dataset that has more than 2 values.
next() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeLearningAlgorithm
nextWithException() - Method in class ai.libs.jaicore.ml.weka.classification.learner.WekaLearningAlgorithm
nextWithException() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm
nextWithException() - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeLearningAlgorithm
nextWithException() - Method in class ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformLearningAlgorithm
nextWithException() - Method in class ai.libs.jaicore.ml.weka.preprocessing.WekaPreprocessorFitter
Normalization - Class in ai.libs.jaicore.ml.weka.classification.pipeline.featurepreprocess
Normalization() - Constructor for class ai.libs.jaicore.ml.weka.classification.pipeline.featurepreprocess.Normalization
normalize(double[]) - Method in class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.Normalizer
Normalizer - Class in ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac
Normalizer(List<ProblemInstance<Instance>>) - Constructor for class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.Normalizer
NUM_THRESH_CANDIDATES - Static variable in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeLearningAlgorithm: Number of threshold candidates created in each tree recursion step.
numBins() - Method in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesLearningAlgorithm.ITimeSeriesBagOfFeaturesConfig: Number of bins used for the CPEs.
numClusters() - Method in interface ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformLearningAlgorithm.IShapeletTransformLearningAlgorithmConfig: Number of shapelet clusters when shapelet clustering is used.
NumericFeatureDomain - Class in ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace: Description of a numeric feature domain.
NumericFeatureDomain(boolean, double, double) - Constructor for class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.NumericFeatureDomain
NumericFeatureDomain(NumericFeatureDomain) - Constructor for class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.NumericFeatureDomain
numFolds() - Method in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesLearningAlgorithm.ITimeSeriesBagOfFeaturesConfig: Number of folds used for the OOB probability estimation in the training phase.
numFolds() - Method in interface ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformLearningAlgorithm.IShapeletTransformLearningAlgorithmConfig: Number of folds used within the MajorityConfidenceVote scheme for the ensembles.
numSegments() - Method in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityLearningAlgorithm.IPatternSimilarityConfig: Number of segments used for feature generation for each tree.
numShapelets() - Method in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.ILearnShapeletsLearningAlgorithmConfig: Parameter which determines how many of the most-informative shapelets should be used.
numShapelets() - Method in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm.ILearnShapeletsLearningAlgorithmConfig: Parameter which determines how many of the most-informative shapelets should be used.
numShapelets() - Method in interface ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformLearningAlgorithm.IShapeletTransformLearningAlgorithmConfig: Number of shapelets extracted in the shapelet search
numTrees() - Method in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityLearningAlgorithm.IPatternSimilarityConfig: Number of trees to be trained.
numTrees() - Method in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesForestLearningAlgorithm.ITimeSeriesForestConfig: Number of trees to be trained.

O

ONEVSREST - ai.libs.jaicore.ml.weka.classification.learner.reduction.EMCNodeType

P

PCA - Class in ai.libs.jaicore.ml.weka.classification.pipeline.featuregen
PCA() - Constructor for class ai.libs.jaicore.ml.weka.classification.pipeline.featuregen.PCA
performSGD(double[][][], double[][][], double[], double[], double[][][], double[][][], double[][], int[][], long, int[]) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm: Method performing the stochastic gradient descent to learn the weights and shapelets.
points - Variable in class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.Kmeans
PolynomialFeatures - Class in ai.libs.jaicore.ml.weka.classification.pipeline.featuregen
PolynomialFeatures() - Constructor for class ai.libs.jaicore.ml.weka.classification.pipeline.featuregen.PolynomialFeatures
predict(double[]) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsClassifier
predict(double[]) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityClassifier: Predicts the class by generated segment and segment difference features based on segments and segmentsDifference.
predict(double[]) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesClassifier: Method predicting the class of the given univInstance.
predict(double[]) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesForestClassifier: Predicts the class of the given instance by taking the majority vote of all trees.
predict(double[]) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeClassifier: Predicts the class of the given univariate instance by iterating through the tree starting from the root node to a leaf node to induce a class prediction.
predict(double[]) - Method in class ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformTSClassifier
predict(TimeSeriesDataset2) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsClassifier
predict(TimeSeriesDataset2) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityClassifier
predict(TimeSeriesDataset2) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesClassifier
predict(TimeSeriesDataset2) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesForestClassifier
predict(TimeSeriesDataset2) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeClassifier
predict(TimeSeriesDataset2) - Method in class ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformTSClassifier
predict(List<double[]>) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsClassifier
predict(List<double[]>) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityClassifier
predict(List<double[]>) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesClassifier
predict(List<double[]>) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesForestClassifier
predict(List<double[]>) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeClassifier
predict(List<double[]>) - Method in class ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformTSClassifier
predict(ILabeledDataset<? extends ILabeledInstance>) - Method in class ai.libs.jaicore.ml.weka.classification.learner.AWekaLearner
predict(ILabeledInstance) - Method in class ai.libs.jaicore.ml.weka.classification.learner.WekaClassifier
predict(ILabeledInstance) - Method in class ai.libs.jaicore.ml.weka.regression.learner.WekaRegressor
predict(ILabeledInstance[]) - Method in class ai.libs.jaicore.ml.weka.classification.learner.AWekaLearner
predict(ILabelRankingInstance) - Method in class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.ModifiedISAC
predict(ILabelRankingInstance[]) - Method in class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.ModifiedISAC
predict(Instance) - Method in class ai.libs.jaicore.ml.weka.RankingByPairwiseComparison
predictInterval(RQPHelper.IntervalAndHeader) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedM5Forest
predictInterval(RQPHelper.IntervalAndHeader) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedM5Tree
predictInterval(RQPHelper.IntervalAndHeader) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedRandomForest
predictInterval(RQPHelper.IntervalAndHeader) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedRandomTree
predictInterval(RQPHelper.IntervalAndHeader) - Method in interface ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.RangeQueryPredictor
predictInterval(Instance) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedM5Forest
predictInterval(Instance) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedRandomForest
predictInterval(Instance) - Method in interface ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.RangeQueryPredictor
PredictionFailedException - Exception in ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree
PredictionFailedException(String) - Constructor for exception ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.PredictionFailedException
PredictionFailedException(String, Throwable) - Constructor for exception ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.PredictionFailedException
PredictionFailedException(Throwable) - Constructor for exception ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.PredictionFailedException
prepare(Instances) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.featuregen.FeatureGeneratorTree
prepare(Instances) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.featuregen.InteractingFeatures
prepare(Instances) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.featuregen.PolynomialFeatures
prepare(Instances) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.featurepreprocess.Normalization
prepare(Instances) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.featurepreprocess.Standardization
prepare(Instances) - Method in interface ai.libs.jaicore.ml.weka.classification.pipeline.FeaturePreprocessor
prepare(Instances) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.MLSophisticatedPipeline
prepare(Instances) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.SupervisedFilterSelector
prepare(Instances) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.SuvervisedFilterPreprocessor
prepareForest(Instances) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedRandomForest: Needs to be called before predicting marginal variance contributions!
preprocess() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedRandomTree: Sets up the tree for fANOVA
PreprocessingException - Exception in ai.libs.jaicore.ml.weka.classification.pipeline
PreprocessingException(String) - Constructor for exception ai.libs.jaicore.ml.weka.classification.pipeline.PreprocessingException
PreprocessingException(String, Throwable) - Constructor for exception ai.libs.jaicore.ml.weka.classification.pipeline.PreprocessingException
PreprocessingException(Throwable) - Constructor for exception ai.libs.jaicore.ml.weka.classification.pipeline.PreprocessingException
printNestedWekaClassifier(Classifier) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
printObservations() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedRandomTree
printSizeOfFeatureSpaceAndPartitioning() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedRandomTree
printSplitPoints() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedRandomTree
printVariances() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedRandomForest
provideCAWPEEnsembleModel(int, int) - Static method in class ai.libs.jaicore.ml.weka.classification.timeseries.learner.ensemble.EnsembleProvider: Initializes the CAWPE ensemble model consisting of five classifiers (SMO, KNN, J48, Logistic and MLP) using a majority voting strategy.
provideHIVECOTEEnsembleModel(long) - Static method in class ai.libs.jaicore.ml.weka.classification.timeseries.learner.ensemble.EnsembleProvider: Initializes the HIVE COTE ensemble consisting of 7 classifiers using a majority voting strategy as described in J.

Q

QuantileAggregator - Class in ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.aggregation: A IntervalAggregator that works based on quantiles.
QuantileAggregator(double) - Constructor for class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.aggregation.QuantileAggregator

R

randomlySampleNoReplacement(List<Integer>, int, long) - Static method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeLearningAlgorithm: Function sampling a given list randomly without replacement using the given seed.
RandomSplitter - Class in ai.libs.jaicore.ml.weka.classification.learner.reduction.splitter
RandomSplitter(Random) - Constructor for class ai.libs.jaicore.ml.weka.classification.learner.reduction.splitter.RandomSplitter
RangeQueryPredictor - Interface in ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree
RankingByPairwiseComparison - Class in ai.libs.jaicore.ml.weka
RankingByPairwiseComparison(RPCConfig) - Constructor for class ai.libs.jaicore.ml.weka.RankingByPairwiseComparison
realizeSplit(IWekaInstances, Collection<Integer>[]) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
realizeSplit(Instances, List<List<Integer>>) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
realizeSplitAsCopiedInstances(IWekaInstances, Collection<Integer>[]) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
realizeSplitAsCopiedInstances(Instances, List<List<Integer>>) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
ReductionGraphGenerator - Class in ai.libs.jaicore.ml.weka.classification.learner.reduction.reducer
ReductionGraphGenerator(Random, Instances) - Constructor for class ai.libs.jaicore.ml.weka.classification.learner.reduction.reducer.ReductionGraphGenerator
ReductionOptimizer - Class in ai.libs.jaicore.ml.weka.classification.learner.reduction.reducer
ReductionOptimizer(long) - Constructor for class ai.libs.jaicore.ml.weka.classification.learner.reduction.reducer.ReductionOptimizer
registerListener(Object) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeLearningAlgorithm
registerListener(Object) - Method in class ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformLearningAlgorithm
regularization() - Method in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.ILearnShapeletsLearningAlgorithmConfig: The regularization used wihtin the SGD.
regularization() - Method in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm.ILearnShapeletsLearningAlgorithmConfig: The regularization used wihtin the SGD.
removeAttribute(Instances, int) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
removeAttributes(Instances, Collection<Integer>) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
removeChild(FeatureGeneratorTree) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.featuregen.FeatureGeneratorTree
removeClassAttribute(Instance) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
removeClassAttribute(Instances) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
removeColumn(int) - Method in class ai.libs.jaicore.ml.weka.dataset.WekaInstance
removeColumn(int) - Method in class ai.libs.jaicore.ml.weka.dataset.WekaInstances
removeColumn(String) - Method in class ai.libs.jaicore.ml.weka.dataset.WekaInstances
removeColumn(IAttribute) - Method in class ai.libs.jaicore.ml.weka.dataset.WekaInstances
removeSelfSimilar(List<Map.Entry<Shapelet, Double>>) - Static method in class ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformLearningAlgorithm: Function removing self-similar shapelets from a list storing shapelet and their quality entries.
RPCConfig - Interface in ai.libs.jaicore.ml.weka
RPNDSplitter - Class in ai.libs.jaicore.ml.weka.classification.learner.reduction.splitter
RPNDSplitter(Random, Classifier) - Constructor for class ai.libs.jaicore.ml.weka.classification.learner.reduction.splitter.RPNDSplitter
RQPHelper - Class in ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.util
RQPHelper.IntervalAndHeader - Class in ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.util

S

sampleIntervals(int, long) - Static method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeLearningAlgorithm: Function sampling intervals based on the length of the time series m and the given seed.
scaleR() - Method in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.ILearnShapeletsLearningAlgorithmConfig: The number of scales used for the shapelet lengths.
scaleR() - Method in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm.ILearnShapeletsLearningAlgorithmConfig: The number of scales used for the shapelet lengths.
schema - Variable in class ai.libs.jaicore.ml.weka.classification.learner.AWekaLearner
setAttributes(List<Attribute>) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityClassifier
setAttributeValue(int, Object) - Method in class ai.libs.jaicore.ml.weka.dataset.WekaInstance
setBaseClassifier(Classifier) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNode
setBaseClassifier(Classifier) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeReD
setC(int) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsClassifier: Setter for LearnShapeletsClassifier.c
setC(int) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm
setClassAttIndexPerTree(int[]) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityClassifier
setClassifier(Classifier) - Method in class ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformTSClassifier: Setter for ShapeletTransformTSClassifier.classifier.
setConfig(Map<String, Object>) - Method in class ai.libs.jaicore.ml.weka.classification.learner.AWekaLearner
setDebug(boolean) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
setEstimateK(boolean) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsClassifier: Enables / disabled the parameter estimation of K within the training algorithm.
setFeatureCaching(boolean) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesForestClassifier
setFeatureSpace(FeatureSpace) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.ExtendedRandomTree
setFinalClf(RandomForest) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesClassifier
setIntervals(int[][][]) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesClassifier
setK(int) - Method in class ai.libs.jaicore.ml.weka.rangequery.ChooseKAugSpaceSampler
setK(int) - Method in class ai.libs.jaicore.ml.weka.rangequery.KNNAugSpaceSampler
setLabel(Object) - Method in class ai.libs.jaicore.ml.weka.dataset.WekaInstance
setLengthPerTree(int[]) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityClassifier
setMax(double) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.NumericFeatureDomain
setMaxDepth(int) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesForestClassifier
setMin(double) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.NumericFeatureDomain
setMinDistanceSearchStrategy(AMinimumDistanceSearchStrategy) - Method in class ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformLearningAlgorithm: Setter for ShapeletTransformLearningAlgorithm.minDistanceSearchStrategy.
setMinShapeLength(int) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsClassifier: Setter for LearnShapeletsClassifier#minShapeLength
setName(String) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.FeatureDomain: Setter for name attribute.
setNodeType(EMCNodeType) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNode
setNumberOfClassifier(int) - Method in class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.ModifiedISACInstanceCollector
setNumberOfTrees(int) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesForestClassifier
setNumBins(int) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesClassifier
setNumClasses(int) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesClassifier
setNumCPUs(int) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeLearningAlgorithm
setPoints(List<double[]>) - Method in class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.ModifiedISACGroupBuilder
setPotence(int) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.featuregen.PolynomialFeatures
setPrepared(boolean) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.SupervisedFilterSelector
setPrepared(boolean) - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.SuvervisedFilterPreprocessor
setS(double[][][]) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsClassifier: Setter for LearnShapeletsClassifier.s
setSeed(int) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesForestClassifier
setSegments(int[][]) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityClassifier
setSegmentsDifference(int[][]) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityClassifier
setShapelets(List<Shapelet>) - Method in class ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformTSClassifier: Setter for ShapeletTransformTSClassifier.shapelets.
setSubsequences(int[][]) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesClassifier
setSubseriesClf(RandomForest) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesClassifier
setTimeout(Timeout) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeLearningAlgorithm
setTrainLeafNodes(int[][][]) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityClassifier
setTrainTargets(int[]) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityClassifier
setTrees(AccessibleRandomTree[]) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.LearnPatternSimilarityClassifier
setTrees(TimeSeriesTreeClassifier[]) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesForestClassifier: Setter for the time series trees.
setupnormalize() - Method in class ai.libs.jaicore.ml.weka.ranking.label.learner.clusterbased.modifiedisac.Normalizer
setUseInstanceReordering(boolean) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm
setValues(double[]) - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.CategoricalFeatureDomain
setW(double[][][]) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsClassifier: Setter for LearnShapeletsClassifier.w
setW0(double[]) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsClassifier: Setter for LearnShapeletsClassifier.w0
shapeletTransform(double[], List<Shapelet>, AMinimumDistanceSearchStrategy) - Static method in class ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformLearningAlgorithm: Function transforming the given instance into the new feature space spanned by the shapelets.
shapeletTransform(TimeSeriesDataset2, List<Shapelet>, Timeout, long, AMinimumDistanceSearchStrategy) - Static method in class ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformLearningAlgorithm: Performs a shapelet transform on a complete dataSet.
ShapeletTransformLearningAlgorithm - Class in ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets: Algorithm training a ShapeletTransform classifier as described in Jason Lines, Luke M.
ShapeletTransformLearningAlgorithm(ShapeletTransformLearningAlgorithm.IShapeletTransformLearningAlgorithmConfig, ShapeletTransformTSClassifier, TimeSeriesDataset2, IQualityMeasure) - Constructor for class ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformLearningAlgorithm: Constructs a training algorithm for the ShapeletTransformTSClassifier classifier specified by the given parameters.
ShapeletTransformLearningAlgorithm.IShapeletTransformLearningAlgorithmConfig - Interface in ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets
ShapeletTransformTSClassifier - Class in ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets: Class for a ShapeletTransform classifier as described in Jason Lines, Luke M.
ShapeletTransformTSClassifier(int, int) - Constructor for class ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformTSClassifier: Constructs an Shapelet Transform classifier using k shapelets, k/2 clusters of the shapelets after shapelet extraction and the FStat quality measure.
ShapeletTransformTSClassifier(int, int, IQualityMeasure, int, boolean) - Constructor for class ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformTSClassifier: Constructs an Shapelet Transform classifier using k shapelets, k/2 clusters of the shapelets after shapelet extraction (if clusterShapelets is true and the quality measure function qm.
ShapeletTransformTSClassifier(int, int, IQualityMeasure, int, boolean, int, int, boolean, int) - Constructor for class ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformTSClassifier: Constructs an Shapelet Transform classifier using k shapelets, k/2 clusters of the shapelets after shapelet extraction (if clusterShapelets is true and the quality measure function qm.
ShapeletTransformTSClassifier(int, IQualityMeasure, int, boolean) - Constructor for class ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformTSClassifier: Constructs an Shapelet Transform classifier using k shapelets, k/2 clusters of the shapelets after shapelet extraction (if clusterShapelets is true and the quality measure function qm.
shuffleAccordingToAlternatingClassScheme(List<Integer>, int[], Random) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm: Shuffles the data in a class alternating scheme.
simplifiedTimeSeriesDatasetToWekaInstances(TimeSeriesDataset2) - Static method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.util.WekaTimeseriesUtil: Converts a given simplified TimeSeriesDataset2 object to a Weka Instances object.
simplifiedTimeSeriesDatasetToWekaInstances(TimeSeriesDataset2, List<String>) - Static method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.util.WekaTimeseriesUtil: Converts a given simplified TimeSeriesDataset2 object to a Weka Instances object.
simplifiedTSInstanceToWekaInstance(double[]) - Static method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.util.WekaTimeseriesUtil: Maps an univariate simplified time series instance to a Weka instance.
singleVariance(double, double, double) - Static method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.AccessibleRandomTree: Computes the variance for a single set
split(Collection<String>, Collection<String>, Collection<String>, Instances) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.splitter.RPNDSplitter
split(Instances) - Method in interface ai.libs.jaicore.ml.weka.classification.learner.reduction.splitter.ISplitter
split(Instances) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.splitter.RandomSplitter
split(Instances) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.splitter.RPNDSplitter
splitToJsonArray(Collection<Integer>[]) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
Standardization - Class in ai.libs.jaicore.ml.weka.classification.pipeline.featurepreprocess
Standardization() - Constructor for class ai.libs.jaicore.ml.weka.classification.pipeline.featurepreprocess.Standardization
substituteInterval(Interval[], Interval, int) - Static method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.util.RQPHelper
successors - Variable in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.AccessibleRandomTree.AccessibleTree: The subtrees appended to this tree.
SupervisedFilterSelector - Class in ai.libs.jaicore.ml.weka.classification.pipeline
SupervisedFilterSelector(ASSearch, ASEvaluation) - Constructor for class ai.libs.jaicore.ml.weka.classification.pipeline.SupervisedFilterSelector
SupervisedFilterSelector(ASSearch, ASEvaluation, AttributeSelection) - Constructor for class ai.libs.jaicore.ml.weka.classification.pipeline.SupervisedFilterSelector
SuvervisedFilterPreprocessor - Class in ai.libs.jaicore.ml.weka.classification.pipeline
SuvervisedFilterPreprocessor(ASSearch, ASEvaluation) - Constructor for class ai.libs.jaicore.ml.weka.classification.pipeline.SuvervisedFilterPreprocessor
SuvervisedFilterPreprocessor(ASSearch, ASEvaluation, AttributeSelection) - Constructor for class ai.libs.jaicore.ml.weka.classification.pipeline.SuvervisedFilterPreprocessor

T

TimeSeriesBagOfFeaturesClassifier - Class in ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees: Implementation of the Time Series Bag-of-Features (TSBF) classifier as described in Baydogan, Mustafa & Runger, George & Tuv, Eugene. (2013).
TimeSeriesBagOfFeaturesClassifier(int) - Constructor for class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesClassifier: Standard constructor using the default parameters (numBins = 10, numFolds = 10, zProp = 0.1, minIntervalLength = 5) for the TSBF classifier.
TimeSeriesBagOfFeaturesClassifier(int, int, int, double, int) - Constructor for class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesClassifier: Constructor specifying parameters (cf.
TimeSeriesBagOfFeaturesClassifier(int, int, int, double, int, boolean) - Constructor for class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesClassifier: Constructor specifying parameters (cf.
TimeSeriesBagOfFeaturesLearningAlgorithm - Class in ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees: Algorithm to train a Time Series Bag-of-Features (TSBF) classifier as described in Baydogan, Mustafa & Runger, George & Tuv, Eugene. (2013).
TimeSeriesBagOfFeaturesLearningAlgorithm(TimeSeriesBagOfFeaturesLearningAlgorithm.ITimeSeriesBagOfFeaturesConfig, TimeSeriesBagOfFeaturesClassifier, TimeSeriesDataset2) - Constructor for class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesLearningAlgorithm: Constructor for a TSBF training algorithm.
TimeSeriesBagOfFeaturesLearningAlgorithm.ITimeSeriesBagOfFeaturesConfig - Interface in ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees
TimeSeriesForestClassifier - Class in ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees: Time series forest classifier as described in Deng, Houtao et al.
TimeSeriesForestClassifier() - Constructor for class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesForestClassifier: Constructing an untrained ensemble of time series trees.
TimeSeriesForestClassifier(TimeSeriesForestLearningAlgorithm.ITimeSeriesForestConfig) - Constructor for class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesForestClassifier: Constructing an untrained ensemble of time series trees.
TimeSeriesForestLearningAlgorithm - Class in ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees: Algorithm to train a time series forest classifier as described in Deng, Houtao et al.
TimeSeriesForestLearningAlgorithm(TimeSeriesForestLearningAlgorithm.ITimeSeriesForestConfig, TimeSeriesForestClassifier, TimeSeriesDataset2) - Constructor for class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesForestLearningAlgorithm: Constructor for a time series forest training algorithm.
TimeSeriesForestLearningAlgorithm.ITimeSeriesForestConfig - Interface in ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees
TimeSeriesTreeClassifier - Class in ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees: Time series tree as described in Deng, Houtao et al.
TimeSeriesTreeClassifier(TimeSeriesTreeLearningAlgorithm.ITimeSeriesTreeConfig) - Constructor for class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeClassifier: Constructs an empty time series tree.
TimeSeriesTreeLearningAlgorithm - Class in ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees: Algorithm to build a time series tree as described in Deng, Houtao et al.
TimeSeriesTreeLearningAlgorithm(TimeSeriesTreeLearningAlgorithm.ITimeSeriesTreeConfig, TimeSeriesTreeClassifier, TimeSeriesDataset2) - Constructor for class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeLearningAlgorithm: Constructor.
TimeSeriesTreeLearningAlgorithm.ITimeSeriesTreeConfig - Interface in ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees
toArray() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.FeatureSpace
toString() - Method in class ai.libs.jaicore.ml.weka.classification.learner.AWekaLearner
toString() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNode
toString() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeLeaf
toString() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeReD
toString() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeReDLeaf
toString() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.MLPipeline
toString() - Method in class ai.libs.jaicore.ml.weka.classification.pipeline.SupervisedFilterSelector
toString() - Method in class ai.libs.jaicore.ml.weka.dataset.WekaInstance
toString() - Method in class ai.libs.jaicore.ml.weka.dataset.WekaInstances
toString() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.CategoricalFeatureDomain
toString() - Method in class ai.libs.jaicore.ml.weka.rangequery.learner.intervaltree.featurespace.NumericFeatureDomain
toStringWithOffset() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNode
toStringWithOffset() - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeReD
toStringWithOffset(String) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNode
toStringWithOffset(String) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeLeaf
toStringWithOffset(String) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeReD
toStringWithOffset(String) - Method in class ai.libs.jaicore.ml.weka.classification.learner.reduction.MCTreeNodeReDLeaf
transformInstances(double[][], Pair<List<Integer>, List<Integer>>) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeLearningAlgorithm: Method transforming the given dataset using the interval pairs specified in T1T2 by calculating each TimeSeriesFeature.FeatureType for every instance and interval pair.
transformInstanceToWekaInstance(ILabeledInstanceSchema, ILabeledInstance) - Static method in class ai.libs.jaicore.ml.weka.dataset.WekaInstancesUtil
transformWEKAAttributeToAttributeType(Attribute) - Static method in class ai.libs.jaicore.ml.weka.dataset.WekaInstancesUtil
tree - Variable in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.AccessibleRandomTree: Internal tree object providing access to leaf node information.
tree(double[][], int[], double, TreeNode<TimeSeriesTreeClassifier.TimeSeriesTreeNodeDecisionFunction>, int) - Method in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeLearningAlgorithm: Tree generation (cf.

U

unscaleParameters(INDArray, DyadMinMaxScaler, int) - Static method in class ai.libs.jaicore.ml.weka.ranking.dyad.learner.zeroshot.util.ZeroShotUtil
USE_BIAS_CORRECTION - Static variable in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.shapelets.LearnShapeletsLearningAlgorithm: Indicator whether Bessel's correction should be used when normalizing arrays.
USE_BIAS_CORRECTION - Static variable in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesLearningAlgorithm: Indicator whether Bessel's correction should in feature generation.
USE_BIAS_CORRECTION - Static variable in class ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeLearningAlgorithm: Indicator that the bias (Bessel's) correction should be used for the calculation of the standard deviation.
useFeatureCaching() - Method in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesForestLearningAlgorithm.ITimeSeriesForestConfig: Indicator whether feature caching should be used.
useFeatureCaching() - Method in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesTreeLearningAlgorithm.ITimeSeriesTreeConfig: Indicator whether feature caching should be used.
useFilterOnSingleInstance(Instance, Filter) - Static method in class ai.libs.jaicore.ml.weka.WekaUtil
useHIVECOTEEnsemble() - Method in interface ai.libs.jaicore.ml.weka.classification.timeseries.learner.shapelets.ShapeletTransformLearningAlgorithm.IShapeletTransformLearningAlgorithmConfig: Indicator whether the HIVE COTE ensemble should be used.

V

V_VOTING_STRATEGY_CLASSIFY - Static variable in interface ai.libs.jaicore.ml.weka.RPCConfig
V_VOTING_STRATEGY_PROBABILITY - Static variable in interface ai.libs.jaicore.ml.weka.RPCConfig
valueOf(String) - Static method in enum ai.libs.jaicore.ml.weka.classification.learner.reduction.EMCNodeType: Returns the enum constant of this type with the specified name.
values() - Static method in enum ai.libs.jaicore.ml.weka.classification.learner.reduction.EMCNodeType: Returns an array containing the constants of this enum type, in the order they are declared.

W

WekaClassifier - Class in ai.libs.jaicore.ml.weka.classification.learner
WekaClassifier(String, String[]) - Constructor for class ai.libs.jaicore.ml.weka.classification.learner.WekaClassifier
WekaClassifier(Classifier) - Constructor for class ai.libs.jaicore.ml.weka.classification.learner.WekaClassifier
WekaInstance - Class in ai.libs.jaicore.ml.weka.dataset
WekaInstance(ILabeledInstanceSchema, ILabeledInstance) - Constructor for class ai.libs.jaicore.ml.weka.dataset.WekaInstance
WekaInstance(Instance) - Constructor for class ai.libs.jaicore.ml.weka.dataset.WekaInstance
WekaInstances - Class in ai.libs.jaicore.ml.weka.dataset
WekaInstances(ILabeledDataset<? extends ILabeledInstance>) - Constructor for class ai.libs.jaicore.ml.weka.dataset.WekaInstances
WekaInstances(Instances) - Constructor for class ai.libs.jaicore.ml.weka.dataset.WekaInstances
WekaInstances(Instances, ILabeledInstanceSchema) - Constructor for class ai.libs.jaicore.ml.weka.dataset.WekaInstances
WekaInstancesFeatureUnion - Class in ai.libs.jaicore.ml.weka
WekaInstancesFeatureUnion() - Constructor for class ai.libs.jaicore.ml.weka.WekaInstancesFeatureUnion
WekaInstancesUtil - Class in ai.libs.jaicore.ml.weka.dataset
WekaLearningAlgorithm - Class in ai.libs.jaicore.ml.weka.classification.learner
WekaLearningAlgorithm(Class<?>, ILabeledDataset<?>) - Constructor for class ai.libs.jaicore.ml.weka.classification.learner.WekaLearningAlgorithm
WekaPreprocessorFitter - Class in ai.libs.jaicore.ml.weka.preprocessing
WekaPreprocessorFitter(ILabeledDataset<?>, String, String) - Constructor for class ai.libs.jaicore.ml.weka.preprocessing.WekaPreprocessorFitter
WekaRegressor - Class in ai.libs.jaicore.ml.weka.regression.learner
WekaRegressor(String, String...) - Constructor for class ai.libs.jaicore.ml.weka.regression.learner.WekaRegressor
WekaRegressor(Classifier) - Constructor for class ai.libs.jaicore.ml.weka.regression.learner.WekaRegressor
WekaTimeseriesUtil - Class in ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.util: WekaUtil
WekaUtil - Class in ai.libs.jaicore.ml.weka
wrappedLearner - Variable in class ai.libs.jaicore.ml.weka.classification.learner.AWekaLearner

Z

ZeroShotUtil - Class in ai.libs.jaicore.ml.weka.ranking.dyad.learner.zeroshot.util: A collection of utility methods used to map the results of a input optimization of PLNetInputOptimizer back to Weka options for the respective classifiers.
zNormalization() - Method in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesLearningAlgorithm.ITimeSeriesBagOfFeaturesConfig: Indicator whether the z transformation should be used for the instances at training and prediction time.
zProportion() - Method in interface ai.libs.jaicore.ml.weka.classification.singlelabel.timeseries.learner.trees.TimeSeriesBagOfFeaturesLearningAlgorithm.ITimeSeriesBagOfFeaturesConfig: Proportion of the total time series length to be used for the subseries generation.

A B C D E F G H I J K L M N O P Q R S T U V W Z
All Classes All Packages