I-Index (ELKI: Environment for DeveLoping KDD-Applications Supported by Index-Structures)

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

I

i - Variable in class elki.clustering.correlation.ORCLUS.ProjectedEnergy: Origin cluster indexes
idmap - Variable in class elki.index.tree.betula.CFTree: Stored leaf entry to dbid relation
ids - Variable in class elki.clustering.dbscan.predicates.AbstractRangeQueryNeighborPredicate.Instance: DBIDs to process
ids - Variable in class elki.clustering.dbscan.predicates.COPACNeighborPredicate.COPACModel: Neighbor ids.
ids - Variable in class elki.clustering.dbscan.predicates.EpsilonNeighborPredicate.Instance: DBIDs to process
ids - Variable in class elki.clustering.dbscan.predicates.PreDeConNeighborPredicate.PreDeConModel: Neighbor ids.
ids - Variable in class elki.clustering.dbscan.predicates.SimilarityNeighborPredicate.Instance: DBIDs to process
ids - Variable in class elki.clustering.hierarchical.AbstractHDBSCAN.HDBSCANAdapter: IDs to process.
ids - Variable in class elki.clustering.hierarchical.ClusterMergeHistory: The initial DBIDs
ids - Variable in class elki.clustering.hierarchical.ClusterMergeHistoryBuilder: The DBIDs in this result.
ids - Variable in class elki.clustering.kmeans.initialization.KMeansPlusPlus.Instance: Object IDs
ids - Variable in class elki.clustering.kmedoids.CLARANS.Assignment: Ids to process.
ids - Variable in class elki.clustering.kmedoids.PAM.Instance: Ids to process.
ids - Variable in class elki.clustering.kmedoids.SingleAssignmentKMedoids.Instance: Ids to process.
ids - Variable in class elki.clustering.optics.ClusterOrder: Cluster order.
ids - Variable in class elki.clustering.optics.GeneralizedOPTICS.Instance: IDs to process.
ids - Variable in class elki.clustering.optics.OPTICSHeap.Instance: IDs to process.
ids - Variable in class elki.clustering.optics.OPTICSList.Instance: IDs to process.
ids - Variable in class elki.clustering.silhouette.FastMSC.Instance: Ids to process.
ids - Variable in class elki.clustering.silhouette.FastMSC.Instance2: Ids to process.
ids - Variable in class elki.clustering.silhouette.PAMSIL.Instance: Ids to process.
ids - Variable in class elki.clustering.subspace.clique.CLIQUEUnit: The ids of the feature vectors this unit contains.
ids - Variable in class elki.clustering.subspace.P3C.ClusterCandidate: Objects contained in cluster.
ids - Variable in class elki.clustering.subspace.P3C.Signature: Object ids.
ids - Variable in class elki.data.Cluster: Cluster data.
IGNORE_NOISE - elki.evaluation.clustering.internal.NoiseHandling: Ignore all noise points
IGNORE_WEIGHT_ID - Static variable in class elki.clustering.kmeans.BetulaLloydKMeans.Par: Ignore cluster weights (naive approach)
ignoreWeight - Variable in class elki.clustering.kmeans.BetulaLloydKMeans: Ignore weight
ignoreWeight - Variable in class elki.clustering.kmeans.BetulaLloydKMeans.Par: Ignore weight
inBoth - Variable in class elki.evaluation.clustering.PairCounting: Pairs in both clusterings.
incrementalUpdateMean(double[], NumberVector, int, double) - Static method in class elki.clustering.kmeans.AbstractKMeans: Compute an incremental update for the mean.
index - Variable in class elki.clustering.optics.FastOPTICS: Index.
index - Variable in class elki.clustering.optics.OPTICSXi.SteepScanPosition: Current position
indices - Variable in class elki.clustering.kmeans.KDTreePruningKMeans.Instance: Array of candidate indexes.
inFirst - Variable in class elki.evaluation.clustering.PairCounting: Pairs in first clustering only.
informationCriterion - Variable in class elki.clustering.kmeans.XMeans: Information criterion to choose the better split.
INIT_ID - Static variable in class elki.clustering.em.BetulaGMM.Par: Parameter to specify the EM cluster models to use.
INIT_ID - Static variable in interface elki.clustering.em.models.BetulaClusterModelFactory: Parameter to specify the cluster center initialization.
INIT_ID - Static variable in interface elki.clustering.em.models.EMClusterModelFactory: Parameter to specify the cluster center initialization.
INIT_ID - Static variable in class elki.clustering.kmeans.FuzzyCMeans.Par: Parameter for k-Means init for initial cluster centers
INIT_ID - Static variable in interface elki.clustering.kmeans.KMeans: Parameter to specify the initialization method
INIT_P - Static variable in class elki.clustering.kmedoids.initialization.AlternateRefinement.Par: Nested inner initialization.
initial(double, boolean) - Method in interface elki.clustering.hierarchical.linkage.Linkage: Initialization of the distance matrix.
initial(double, boolean) - Method in class elki.clustering.hierarchical.linkage.MinimumVarianceLinkage
initial(double, boolean) - Method in class elki.clustering.hierarchical.linkage.WardLinkage
INITIAL_MEANS - Static variable in class elki.clustering.kmeans.initialization.Predefined.Par: Option to specify the initial means to use.
initialAssignToNearestCluster() - Method in class elki.clustering.kmeans.AnnulusKMeans.Instance
initialAssignToNearestCluster() - Method in class elki.clustering.kmeans.ElkanKMeans.Instance
initialAssignToNearestCluster() - Method in class elki.clustering.kmeans.ExponionKMeans.Instance
initialAssignToNearestCluster() - Method in class elki.clustering.kmeans.HamerlyKMeans.Instance: Perform initial cluster assignment.
initialAssignToNearestCluster() - Method in class elki.clustering.kmeans.HartiganWongKMeans.Instance: Step 1: For each point I, find its two closest centers, IC1(I) and IC2(I).
initialAssignToNearestCluster() - Method in class elki.clustering.kmeans.ShallotKMeans.Instance
initialAssignToNearestCluster() - Method in class elki.clustering.kmeans.SimplifiedElkanKMeans.Instance: Perform initial cluster assignment.
initialAssignToNearestCluster() - Method in class elki.clustering.kmeans.spherical.EuclideanSphericalElkanKMeans.Instance
initialAssignToNearestCluster() - Method in class elki.clustering.kmeans.spherical.EuclideanSphericalHamerlyKMeans.Instance: Perform initial cluster assignment.
initialAssignToNearestCluster() - Method in class elki.clustering.kmeans.spherical.EuclideanSphericalSimplifiedElkanKMeans.Instance: Perform initial cluster assignment.
initialAssignToNearestCluster() - Method in class elki.clustering.kmeans.spherical.SphericalElkanKMeans.Instance
initialAssignToNearestCluster() - Method in class elki.clustering.kmeans.spherical.SphericalHamerlyKMeans.Instance: Perform initial cluster assignment.
initialAssignToNearestCluster() - Method in class elki.clustering.kmeans.spherical.SphericalSimplifiedElkanKMeans.Instance: Perform initial cluster assignment.
initialAssignToNearestCluster() - Method in class elki.clustering.kmeans.spherical.SphericalSimplifiedHamerlyKMeans.Instance: Perform initial cluster assignment.
initialAssignToNearestCluster() - Method in class elki.clustering.kmeans.YinYangKMeans.Instance: Perform initial cluster assignment,
initialDBID(DBIDRef) - Method in class elki.clustering.correlation.HiCO.Instance
initialDBID(DBIDRef) - Method in class elki.clustering.optics.GeneralizedOPTICS.Instance: Initialize for a new DBID.
initialDBID(DBIDRef) - Method in class elki.clustering.subspace.HiSC.Instance
initialGroupAssignment(int, double[][], int[]) - Method in class elki.clustering.kmeans.YinYangKMeans.Instance: Initial k-means assignment for centers to groups.
initialization - Variable in class elki.clustering.affinitypropagation.AffinityPropagation: Similarity initialization
initialization - Variable in class elki.clustering.em.BetulaGMM.Par: initialization method
initialization - Variable in class elki.clustering.hierarchical.birch.BIRCHLloydKMeans: k-means++ initialization
initialization - Variable in class elki.clustering.hierarchical.birch.BIRCHLloydKMeans.Par: initialization method
initialization - Variable in class elki.clustering.kmeans.BetulaLloydKMeans: k-means++ initialization
initialization - Variable in class elki.clustering.kmeans.BetulaLloydKMeans.Par: initialization method
initialize() - Method in class elki.clustering.kmeans.HartiganWongKMeans.Instance: Initialize AN1, AN2, ITRAN, NCP
initializeDistanceMatrix(ArrayDBIDs, DistanceQuery<?>, Linkage) - Static method in class elki.clustering.hierarchical.AGNES: Initialize a distance matrix.
initializeMatrices(ArrayDBIDs, ArrayModifiableDBIDs, DistanceQuery<O>) - Static method in class elki.clustering.hierarchical.MiniMax: Initializes the inter-cluster distance matrix of possible merges
initializeNNCache(double[], double[], int[]) - Static method in class elki.clustering.hierarchical.Anderberg.Instance: Initialize the NN cache.
initializer - Variable in class elki.clustering.em.BetulaGMM: Maximum number of iterations.
initializer - Variable in class elki.clustering.em.models.BetulaDiagonalGaussianModelFactory: Class to choose the initial means
initializer - Variable in class elki.clustering.em.models.BetulaDiagonalGaussianModelFactory.Par: Initialization method
initializer - Variable in class elki.clustering.em.models.BetulaMultivariateGaussianModelFactory: Class to choose the initial means
initializer - Variable in class elki.clustering.em.models.BetulaMultivariateGaussianModelFactory.Par: Initialization method
initializer - Variable in class elki.clustering.em.models.BetulaSphericalGaussianModelFactory: Class to choose the initial means
initializer - Variable in class elki.clustering.em.models.BetulaSphericalGaussianModelFactory.Par: Initialization method
initializer - Variable in class elki.clustering.em.models.DiagonalGaussianModelFactory: Class to choose the initial means
initializer - Variable in class elki.clustering.em.models.MultivariateGaussianModelFactory: Class to choose the initial means
initializer - Variable in class elki.clustering.em.models.SphericalGaussianModelFactory: Class to choose the initial means
initializer - Variable in class elki.clustering.em.models.TextbookMultivariateGaussianModelFactory: Class to choose the initial means
initializer - Variable in class elki.clustering.em.models.TextbookSphericalGaussianModelFactory: Class to choose the initial means
initializer - Variable in class elki.clustering.em.models.TwoPassMultivariateGaussianModelFactory: Class to choose the initial means
initializer - Variable in class elki.clustering.kmeans.AbstractKMeans: Method to choose initial means.
initializer - Variable in class elki.clustering.kmeans.AbstractKMeans.Par: Initialization method.
initializer - Variable in class elki.clustering.kmeans.FuzzyCMeans: Produces initial cluster.
initializer - Variable in class elki.clustering.kmeans.FuzzyCMeans.Par: K-Means init for initial cluster centers
initializer - Variable in class elki.clustering.kmedoids.AlternatingKMedoids: Method to choose initial means.
initializer - Variable in class elki.clustering.kmedoids.AlternatingKMedoids.Par: Initialization method.
initializer - Variable in class elki.clustering.kmedoids.PAM: Method to choose initial means.
initializer - Variable in class elki.clustering.kmedoids.PAM.Par: Method to choose initial means.
initialMeans - Variable in class elki.clustering.kmeans.initialization.Predefined: Initial means to return.
initialMeans - Variable in class elki.clustering.kmeans.initialization.Predefined.Par: Initial means.
initialMeans(Relation<V>) - Method in class elki.clustering.kmeans.AbstractKMeans: Choose the initial means.
initialMedoids(DistanceQuery<? super O>, DBIDs, int) - Method in class elki.clustering.kmedoids.PAM: Choose the initial medoids.
initialSeeds(Relation<? extends NumberVector>, int) - Method in class elki.clustering.correlation.ORCLUS: Initializes the list of seeds wit a random sample of size k.
initialSeparation(double[][]) - Method in class elki.clustering.kmeans.spherical.SphericalKMeans.Instance: Initial separation of means.
initialSeperation(double[][]) - Method in class elki.clustering.kmeans.AbstractKMeans.Instance: Initial separation of means.
initialSet(DBIDs, int, Random) - Method in class elki.clustering.subspace.PROCLUS: Returns a set of k elements from the specified sample set.
initialWeights(double[], double[][]) - Method in class elki.clustering.hierarchical.birch.BIRCHKMeansPlusPlus: Initialize the weight list.
initialWeights(NumberVector) - Method in class elki.clustering.kmeans.initialization.KMC2.Instance: Initialize the weight list.
initialWeights(NumberVector) - Method in class elki.clustering.kmeans.initialization.SphericalAFKMC2.Instance
initialWeights(NumberVector) - Method in class elki.clustering.kmeans.initialization.SphericalKMeansPlusPlus.Instance: Initialize the weight list.
initialWeights(ClusterFeature, List<? extends AsClusterFeature>, double[]) - Method in class elki.clustering.kmeans.initialization.betula.CFKPlusPlusLeaves: Initialize the weight list.
initialWeights(T) - Method in class elki.clustering.kmeans.initialization.KMeansPlusPlus.Instance: Initialize the weight list.
initOneDimensionalUnits(Relation<? extends NumberVector>) - Method in class elki.clustering.subspace.CLIQUE: Initializes and returns the one dimensional units.
initStream(InputStream) - Method in class elki.datasource.parser.ClusteringVectorParser
inner - Variable in class elki.clustering.hierarchical.OPTICSToHierarchical: Inner OPTICS clustering algorithm.
inner - Variable in class elki.clustering.hierarchical.OPTICSToHierarchical.Par: Inner OPTICS clustering algorithm.
inner - Variable in class elki.clustering.kmedoids.CLARA.CachedDistanceQuery: Inner distance query
inner - Variable in class elki.clustering.kmedoids.initialization.AlternateRefinement: Inner initialization.
inner - Variable in class elki.clustering.kmedoids.initialization.AlternateRefinement.Par: Inner initialization.
inner - Variable in class elki.clustering.kmedoids.initialization.KMedoidsKMedoidsInitialization: Inner k-medoids clustering to use.
inner - Variable in class elki.clustering.kmedoids.initialization.KMedoidsKMedoidsInitialization.Par: Clustering algorithm
inner - Variable in class elki.evaluation.clustering.extractor.CutDendrogramByHeightExtractor: Class to perform the cluster extraction.
inner - Variable in class elki.evaluation.clustering.extractor.CutDendrogramByHeightExtractor.Par: Inner algorithm to extract a clustering.
inner - Variable in class elki.evaluation.clustering.extractor.CutDendrogramByNumberOfClustersExtractor: Class to perform the cluster extraction.
inner - Variable in class elki.evaluation.clustering.extractor.CutDendrogramByNumberOfClustersExtractor.Par: Inner algorithm to extract a clustering.
inner - Variable in class elki.evaluation.clustering.extractor.HDBSCANHierarchyExtractionEvaluator: Class to perform the cluster extraction.
inner - Variable in class elki.evaluation.clustering.extractor.HDBSCANHierarchyExtractionEvaluator.Par: Inner algorithm to extract a clustering.
inner - Variable in class elki.evaluation.clustering.extractor.SimplifiedHierarchyExtractionEvaluator: Class to perform the cluster extraction.
inner - Variable in class elki.evaluation.clustering.extractor.SimplifiedHierarchyExtractionEvaluator.Par: Inner algorithm to extract a clustering.
INNER_ID - Static variable in class elki.clustering.kmedoids.initialization.KMedoidsKMedoidsInitialization.Par: Option ID for the nested k-medoids clustering algorithm.
innerkMeans - Variable in class elki.clustering.kmeans.BestOfMultipleKMeans: Variant of kMeans for the bisecting step.
innerkMeans - Variable in class elki.clustering.kmeans.BisectingKMeans: Variant of kMeans for the bisecting step.
innerkMeans - Variable in class elki.clustering.kmeans.initialization.SampleKMeans: Variant of kMeans to use for initialization.
innerKMeans - Variable in class elki.clustering.kmeans.XMeans: Inner k-means algorithm.
inNone - Variable in class elki.evaluation.clustering.PairCounting: Pairs in neither clusterings.
inSecond - Variable in class elki.evaluation.clustering.PairCounting: Pairs in second clustering only.
insert(CFTree.TreeNode, ClusteringFeature) - Method in class elki.clustering.hierarchical.birch.CFTree: Recursive insertion.
insert(CFTree.TreeNode, NumberVector) - Method in class elki.clustering.hierarchical.birch.CFTree: Recursive insertion.
insert(NumberVector) - Method in class elki.clustering.hierarchical.birch.CFTree: Insert a data point into the tree.
insert(NumberVector, DBIDRef) - Method in class elki.index.tree.betula.CFTree: Insert a data point into the tree.
insert(CFNode<L>, NumberVector, DBIDRef) - Method in class elki.index.tree.betula.CFTree: Recursive insertion.
insert(CFNode<L>, AsClusterFeature) - Method in class elki.index.tree.betula.CFTree: Recursive insertion.
insertIntoGrid(DBIDRef, V, int, int) - Method in class elki.clustering.dbscan.GriDBSCAN.Instance: Insert a single object into the grid; potentially into multiple cells (at most 2^d) via recursion.
Instance() - Constructor for class elki.clustering.dbscan.DBSCAN.Instance
Instance() - Constructor for class elki.clustering.hierarchical.MedoidLinkage.Instance: Constructor.
Instance() - Constructor for class elki.clustering.hierarchical.MiniMax.Instance: Constructor.
Instance() - Constructor for class elki.clustering.hierarchical.MiniMaxAnderberg.Instance
Instance() - Constructor for class elki.clustering.hierarchical.MiniMaxNNChain.Instance
Instance(double, RangeSearcher<DBIDRef>, DBIDs) - Constructor for class elki.clustering.dbscan.predicates.EpsilonNeighborPredicate.Instance: Constructor.
Instance(double, RangeSearcher<DBIDRef>, DBIDs) - Constructor for class elki.clustering.dbscan.predicates.SimilarityNeighborPredicate.Instance: Constructor.
Instance(int) - Constructor for class elki.clustering.dbscan.predicates.MinPtsCorePredicate.Instance: Constructor for this predicate.
Instance(FourC.Settings) - Constructor for class elki.clustering.dbscan.predicates.FourCCorePredicate.Instance: Constructor for this predicate.
Instance(NeighborPredicate.Instance<T>, CorePredicate.Instance<? super T>, boolean) - Constructor for class elki.clustering.dbscan.GeneralizedDBSCAN.Instance: Full Constructor
Instance(ClusterMergeHistory) - Constructor for class elki.clustering.hierarchical.extraction.AbstractCutDendrogram.Instance: Constructor.
Instance(ClusterMergeHistory) - Constructor for class elki.clustering.hierarchical.extraction.ClustersWithNoiseExtraction.Instance: Constructor.
Instance(ClusterMergeHistory) - Constructor for class elki.clustering.hierarchical.extraction.CutDendrogramByHeight.Instance: Constructor.
Instance(ClusterMergeHistory) - Constructor for class elki.clustering.hierarchical.extraction.CutDendrogramByNumberOfClusters.Instance: Constructor.
Instance(ClusterMergeHistory) - Constructor for class elki.clustering.hierarchical.extraction.HDBSCANHierarchyExtraction.Instance: Constructor.
Instance(ClusterMergeHistory) - Constructor for class elki.clustering.hierarchical.extraction.SimplifiedHierarchyExtraction.Instance: Constructor.
Instance(HACAM.Variant) - Constructor for class elki.clustering.hierarchical.HACAM.Instance: Constructor.
Instance(GeometricLinkage) - Constructor for class elki.clustering.hierarchical.LinearMemoryNNChain.Instance: Constructor.
Instance(Linkage) - Constructor for class elki.clustering.hierarchical.AGNES.Instance: Constructor.
Instance(Linkage) - Constructor for class elki.clustering.hierarchical.Anderberg.Instance: Constructor.
Instance(Linkage) - Constructor for class elki.clustering.hierarchical.NNChain.Instance: Constructor.
Instance(PreDeCon.Settings) - Constructor for class elki.clustering.dbscan.predicates.PreDeConCorePredicate.Instance: Constructor for this predicate.
Instance(Database, NeighborPredicate<T>, CorePredicate<? super T>, boolean) - Constructor for class elki.clustering.dbscan.parallel.ParallelGeneralizedDBSCAN.Instance: Full Constructor
Instance(DBIDs) - Constructor for class elki.clustering.optics.GeneralizedOPTICS.Instance: Constructor for a single data set.
Instance(DBIDs, DataStore<COPACNeighborPredicate.COPACModel>) - Constructor for class elki.clustering.dbscan.predicates.COPACNeighborPredicate.Instance: Constructor.
Instance(DBIDs, DataStore<PreDeConNeighborPredicate.PreDeConModel>) - Constructor for class elki.clustering.dbscan.predicates.FourCNeighborPredicate.Instance: Constructor.
Instance(DBIDs, DataStore<PreDeConNeighborPredicate.PreDeConModel>) - Constructor for class elki.clustering.dbscan.predicates.PreDeConNeighborPredicate.Instance: Constructor.
Instance(DBIDs, DataStore<PCAFilteredResult>, Relation<? extends NumberVector>) - Constructor for class elki.clustering.dbscan.predicates.ERiCNeighborPredicate.Instance: Constructor.
Instance(DBIDs, DataStore<M>) - Constructor for class elki.clustering.dbscan.predicates.AbstractRangeQueryNeighborPredicate.Instance: Constructor.
Instance(DBIDs, RandomFactory) - Constructor for class elki.clustering.kmeans.initialization.KMeansPlusPlus.Instance: Constructor.
Instance(DistanceQuery<?>, DBIDs, WritableIntegerDataStore) - Constructor for class elki.clustering.kmedoids.EagerPAM.Instance: Constructor.
Instance(DistanceQuery<?>, DBIDs, WritableIntegerDataStore) - Constructor for class elki.clustering.kmedoids.FasterPAM.Instance: Constructor.
Instance(DistanceQuery<?>, DBIDs, WritableIntegerDataStore) - Constructor for class elki.clustering.kmedoids.FastPAM1.Instance: Constructor.
Instance(DistanceQuery<?>, DBIDs, WritableIntegerDataStore) - Constructor for class elki.clustering.kmedoids.PAM.Instance: Constructor.
Instance(DistanceQuery<?>, DBIDs, WritableIntegerDataStore) - Constructor for class elki.clustering.kmedoids.ReynoldsPAM.Instance: Constructor.
Instance(DistanceQuery<?>, DBIDs, WritableIntegerDataStore) - Constructor for class elki.clustering.kmedoids.SingleAssignmentKMedoids.Instance: Constructor.
Instance(DistanceQuery<?>, DBIDs, WritableIntegerDataStore) - Constructor for class elki.clustering.silhouette.FasterMSC.Instance: Constructor.
Instance(DistanceQuery<?>, DBIDs, WritableIntegerDataStore) - Constructor for class elki.clustering.silhouette.FastMSC.Instance: Constructor.
Instance(DistanceQuery<?>, DBIDs, WritableIntegerDataStore) - Constructor for class elki.clustering.silhouette.PAMMEDSIL.Instance: Constructor.
Instance(DistanceQuery<?>, DBIDs, WritableIntegerDataStore) - Constructor for class elki.clustering.silhouette.PAMSIL.Instance: Constructor.
Instance(DistanceQuery<?>, DBIDs, WritableIntegerDataStore, double) - Constructor for class elki.clustering.kmedoids.FastPAM.Instance: Constructor.
Instance(Relation<? extends NumberVector>) - Constructor for class elki.clustering.correlation.HiCO.Instance: Constructor.
Instance(Relation<? extends NumberVector>) - Constructor for class elki.clustering.subspace.HiSC.Instance: Constructor.
Instance(Relation<? extends NumberVector>, double[][]) - Constructor for class elki.clustering.kmeans.spherical.EuclideanSphericalElkanKMeans.Instance: Constructor.
Instance(Relation<? extends NumberVector>, double[][]) - Constructor for class elki.clustering.kmeans.spherical.EuclideanSphericalHamerlyKMeans.Instance: Constructor.
Instance(Relation<? extends NumberVector>, double[][]) - Constructor for class elki.clustering.kmeans.spherical.EuclideanSphericalSimplifiedElkanKMeans.Instance: Constructor.
Instance(Relation<? extends NumberVector>, double[][]) - Constructor for class elki.clustering.kmeans.spherical.SphericalElkanKMeans.Instance: Constructor.
Instance(Relation<? extends NumberVector>, double[][]) - Constructor for class elki.clustering.kmeans.spherical.SphericalHamerlyKMeans.Instance: Constructor.
Instance(Relation<? extends NumberVector>, double[][]) - Constructor for class elki.clustering.kmeans.spherical.SphericalKMeans.Instance: Constructor.
Instance(Relation<? extends NumberVector>, double[][]) - Constructor for class elki.clustering.kmeans.spherical.SphericalSimplifiedElkanKMeans.Instance: Constructor.
Instance(Relation<? extends NumberVector>, double[][]) - Constructor for class elki.clustering.kmeans.spherical.SphericalSimplifiedHamerlyKMeans.Instance: Constructor.
Instance(Relation<? extends NumberVector>, double[][]) - Constructor for class elki.clustering.kmeans.spherical.SphericalSingleAssignmentKMeans.Instance: Constructor.
Instance(Relation<? extends NumberVector>, double, RandomFactory) - Constructor for class elki.clustering.kmeans.initialization.SphericalKMeansPlusPlus.Instance: Constructor.
Instance(Relation<? extends NumberVector>, int, double, RandomFactory) - Constructor for class elki.clustering.kmeans.initialization.SphericalAFKMC2.Instance: Constructor.
Instance(Relation<? extends NumberVector>, NumberVectorDistance<?>, double[][]) - Constructor for class elki.clustering.kmeans.AbstractKMeans.Instance: Constructor.
Instance(Relation<? extends NumberVector>, NumberVectorDistance<?>, double[][]) - Constructor for class elki.clustering.kmeans.AnnulusKMeans.Instance: Constructor.
Instance(Relation<? extends NumberVector>, NumberVectorDistance<?>, double[][]) - Constructor for class elki.clustering.kmeans.CompareMeans.Instance: Constructor.
Instance(Relation<? extends NumberVector>, NumberVectorDistance<?>, double[][]) - Constructor for class elki.clustering.kmeans.ElkanKMeans.Instance: Constructor.
Instance(Relation<? extends NumberVector>, NumberVectorDistance<?>, double[][]) - Constructor for class elki.clustering.kmeans.ExponionKMeans.Instance: Constructor.
Instance(Relation<? extends NumberVector>, NumberVectorDistance<?>, double[][]) - Constructor for class elki.clustering.kmeans.HamerlyKMeans.Instance: Constructor.
Instance(Relation<? extends NumberVector>, NumberVectorDistance<?>, double[][]) - Constructor for class elki.clustering.kmeans.HartiganWongKMeans.Instance: Constructor.
Instance(Relation<? extends NumberVector>, NumberVectorDistance<?>, double[][]) - Constructor for class elki.clustering.kmeans.KDTreeFilteringKMeans.Instance: Constructor.
Instance(Relation<? extends NumberVector>, NumberVectorDistance<?>, double[][]) - Constructor for class elki.clustering.kmeans.KDTreePruningKMeans.Instance: Constructor.
Instance(Relation<? extends NumberVector>, NumberVectorDistance<?>, double[][]) - Constructor for class elki.clustering.kmeans.KMeansMinusMinus.Instance: Constructor.
Instance(Relation<? extends NumberVector>, NumberVectorDistance<?>, double[][]) - Constructor for class elki.clustering.kmeans.KMediansLloyd.Instance: Constructor.
Instance(Relation<? extends NumberVector>, NumberVectorDistance<?>, double[][]) - Constructor for class elki.clustering.kmeans.LloydKMeans.Instance: Constructor.
Instance(Relation<? extends NumberVector>, NumberVectorDistance<?>, double[][]) - Constructor for class elki.clustering.kmeans.MacQueenKMeans.Instance: Constructor.
Instance(Relation<? extends NumberVector>, NumberVectorDistance<?>, double[][]) - Constructor for class elki.clustering.kmeans.ShallotKMeans.Instance: Constructor.
Instance(Relation<? extends NumberVector>, NumberVectorDistance<?>, double[][]) - Constructor for class elki.clustering.kmeans.SimplifiedElkanKMeans.Instance: Constructor.
Instance(Relation<? extends NumberVector>, NumberVectorDistance<?>, double[][]) - Constructor for class elki.clustering.kmeans.SingleAssignmentKMeans.Instance: Constructor.
Instance(Relation<? extends NumberVector>, NumberVectorDistance<?>, double[][]) - Constructor for class elki.clustering.kmeans.SortMeans.Instance: Constructor.
Instance(Relation<? extends NumberVector>, NumberVectorDistance<?>, double[][], int) - Constructor for class elki.clustering.kmeans.YinYangKMeans.Instance: Constructor.
Instance(Relation<? extends NumberVector>, NumberVectorDistance<?>, int, RandomFactory) - Constructor for class elki.clustering.kmeans.initialization.AFKMC2.Instance: Constructor.
Instance(Relation<? extends NumberVector>, NumberVectorDistance<?>, int, RandomFactory) - Constructor for class elki.clustering.kmeans.initialization.KMC2.Instance: Constructor.
Instance(Relation<O>) - Constructor for class elki.clustering.optics.OPTICSHeap.Instance: Constructor for a single data set.
Instance(Relation<O>) - Constructor for class elki.clustering.optics.OPTICSList.Instance: Constructor for a single data set.
Instance(Relation<V>, NumberVectorDistance<? super V>, WritableIntegerDataStore, double[][]) - Constructor for class elki.clustering.kmeans.parallel.KMeansProcessor.Instance: Constructor.
Instance(Distance<? super V>, double, int, double) - Constructor for class elki.clustering.dbscan.GriDBSCAN.Instance: Constructor.
Instance2(DistanceQuery<?>, DBIDs, WritableIntegerDataStore) - Constructor for class elki.clustering.silhouette.FasterMSC.Instance2: Constructor.
Instance2(DistanceQuery<?>, DBIDs, WritableIntegerDataStore) - Constructor for class elki.clustering.silhouette.FastMSC.Instance2: Constructor.
instantiate(Database) - Method in class elki.clustering.dbscan.predicates.COPACNeighborPredicate
instantiate(Database) - Method in interface elki.clustering.dbscan.predicates.CorePredicate: Instantiate for a database.
instantiate(Database) - Method in class elki.clustering.dbscan.predicates.EpsilonNeighborPredicate
instantiate(Database) - Method in class elki.clustering.dbscan.predicates.ERiCNeighborPredicate
instantiate(Database) - Method in class elki.clustering.dbscan.predicates.FourCCorePredicate
instantiate(Database) - Method in class elki.clustering.dbscan.predicates.FourCNeighborPredicate
instantiate(Database) - Method in class elki.clustering.dbscan.predicates.MinPtsCorePredicate
instantiate(Database) - Method in interface elki.clustering.dbscan.predicates.NeighborPredicate: Instantiate for a database.
instantiate(Database) - Method in class elki.clustering.dbscan.predicates.PreDeConCorePredicate
instantiate(Database) - Method in class elki.clustering.dbscan.predicates.PreDeConNeighborPredicate
instantiate(Database) - Method in class elki.clustering.dbscan.predicates.SimilarityNeighborPredicate
instantiate(Relation<? extends NumberVector>) - Method in class elki.clustering.dbscan.predicates.COPACNeighborPredicate: Full instantiation method.
instantiate(Relation<? extends NumberVector>) - Method in class elki.clustering.dbscan.predicates.ERiCNeighborPredicate: Full instantiation interface.
instantiate(Relation<T>) - Method in class elki.similarity.cluster.ClusteringAdjustedRandIndexSimilarity
instantiate(Relation<T>) - Method in class elki.similarity.cluster.ClusteringBCubedF1Similarity
instantiate(Relation<T>) - Method in interface elki.similarity.cluster.ClusteringDistanceSimilarity
instantiate(Relation<T>) - Method in class elki.similarity.cluster.ClusteringFowlkesMallowsSimilarity
instantiate(Relation<T>) - Method in class elki.similarity.cluster.ClusteringRandIndexSimilarity
instantiate(Relation<T>) - Method in class elki.similarity.cluster.ClusterIntersectionSimilarity
instantiate(Relation<T>) - Method in class elki.similarity.cluster.ClusterJaccardSimilarity
instantiate(Executor) - Method in class elki.clustering.dbscan.parallel.ParallelGeneralizedDBSCAN.Instance
instantiate(Executor) - Method in class elki.clustering.kmeans.parallel.KMeansProcessor
InterclusterWeight - Class in elki.clustering.kmeans.initialization.betula: Initialization via n2 * D2²(cf1, cf2), which supposedly is closes to the idea of k-means++ initialization.
InterclusterWeight() - Constructor for class elki.clustering.kmeans.initialization.betula.InterclusterWeight
inverseDensities - Variable in class elki.clustering.optics.FastOPTICS: Inverse Densities correspond to average distances in point set of projections
inversePurity() - Method in class elki.evaluation.clustering.SetMatchingPurity: Get the set matchings inverse purity (second:first clustering) (normalized, 1 = equal)
invertedRows - Variable in class elki.data.model.BiclusterWithInversionsModel: The ids of inverted rows.
invertRow(int, boolean) - Method in class elki.clustering.biclustering.ChengAndChurch.BiclusterCandidate
ipiPow - Variable in class elki.clustering.em.KDTreeEM: Gaussian scaling factor for likelihood.
irow - Variable in class elki.clustering.biclustering.ChengAndChurch.BiclusterCandidate: Row and column bitmasks.
isAssigned() - Method in class elki.clustering.subspace.clique.CLIQUEUnit: Returns true if this unit is already assigned to a cluster.
isBetter(double, double) - Method in class elki.clustering.kmeans.quality.AkaikeInformationCriterion
isBetter(double, double) - Method in class elki.clustering.kmeans.quality.AkaikeInformationCriterionXMeans
isBetter(double, double) - Method in class elki.clustering.kmeans.quality.BayesianInformationCriterion
isBetter(double, double) - Method in class elki.clustering.kmeans.quality.BayesianInformationCriterionXMeans
isBetter(double, double) - Method in class elki.clustering.kmeans.quality.BayesianInformationCriterionZhao
isBetter(double, double) - Method in interface elki.clustering.kmeans.quality.KMeansQualityMeasure: Compare two scores.
isBetter(double, double) - Method in class elki.clustering.kmeans.quality.WithinClusterMeanDistance
isBetter(double, double) - Method in class elki.clustering.kmeans.quality.WithinClusterVariance
isCorePoint(DBIDRef, PreDeConNeighborPredicate.PreDeConModel) - Method in class elki.clustering.dbscan.predicates.FourCCorePredicate.Instance
isCorePoint(DBIDRef, PreDeConNeighborPredicate.PreDeConModel) - Method in class elki.clustering.dbscan.predicates.PreDeConCorePredicate.Instance
isCorePoint(DBIDRef, DBIDs) - Method in class elki.clustering.dbscan.predicates.MinPtsCorePredicate.Instance
isCorePoint(DBIDRef, T) - Method in interface elki.clustering.dbscan.predicates.CorePredicate.Instance: Decide whether the point is a core point, based on its neighborhood.
isEmpty() - Method in class elki.clustering.dbscan.predicates.COPACNeighborPredicate.COPACModel
isFarther(double[], double[], double[], double[]) - Method in class elki.clustering.kmeans.KDTreeFilteringKMeans.Instance: Check if a cluster mean is farther than another.
isLocalMaximum(double, DBIDs, WritableDoubleDataStore) - Method in class elki.clustering.dbscan.LSDBC: Test if a point is a local density maximum.
isMetric() - Method in class elki.similarity.cluster.ClusteringAdjustedRandIndexSimilarity
isMetric() - Method in class elki.similarity.cluster.ClusteringBCubedF1Similarity
isMetric() - Method in class elki.similarity.cluster.ClusteringFowlkesMallowsSimilarity
isMetric() - Method in class elki.similarity.cluster.ClusteringRandIndexSimilarity
isMetric() - Method in class elki.similarity.cluster.ClusterIntersectionSimilarity
isMetric() - Method in class elki.similarity.cluster.ClusterJaccardSimilarity
isNoise() - Method in class elki.data.Cluster: Getter for noise flag.
isNone() - Method in class elki.evaluation.clustering.pairsegments.Segment: Check if this segment contains the pairs that are never clustered by any of the clusterings (all 0).
isNotSpurious(int) - Method in class elki.clustering.hierarchical.extraction.SimplifiedHierarchyExtraction.TempCluster: Test if a cluster is spurious.
isParent(ERiCNeighborPredicate.Instance, Cluster<CorrelationModel>, It<Cluster<CorrelationModel>>) - Method in class elki.clustering.correlation.ERiC: Returns true, if the specified parent cluster is a parent of one child of the children clusters.
isReferenceResult(Clustering<?>) - Method in class elki.evaluation.clustering.EvaluateClustering: Test if a clustering result is a valid reference result.
isSoft() - Method in class elki.clustering.em.BetulaGMM
isSpurious(int) - Method in class elki.clustering.hierarchical.extraction.HDBSCANHierarchyExtraction.TempCluster: Test if a cluster is spurious.
isSpurious(HDBSCANHierarchyExtraction.TempCluster, boolean) - Method in class elki.clustering.hierarchical.extraction.HDBSCANHierarchyExtraction.Instance: Spurious, also for non-materialized clusters.
isSquared - Variable in class elki.clustering.hierarchical.ClusterMergeHistory: Flag to indicate squared values
isSquared - Variable in class elki.clustering.hierarchical.ClusterMergeHistoryBuilder: Flag to indicate squared distances.
isSquared - Variable in class elki.clustering.kmeans.AbstractKMeans.Instance: Indicates whether the distance function is squared.
isSquared() - Method in class elki.clustering.hierarchical.ClusterMergeHistory: Indicate whether the stored values are squared values.
isStrictPartitioning() - Method in class elki.evaluation.clustering.ClusterContingencyTable: Check whether the marginal cluster sizes both sum to the total size.
isSubspace(Subspace) - Method in class elki.data.Subspace: Returns true if this subspace is a subspace of the specified subspace, i.e.
isSuperset(P3C.Signature) - Method in class elki.clustering.subspace.P3C.Signature: Test whether this is a superset of the other signature.
isSymmetric() - Method in interface elki.similarity.cluster.ClusteringDistanceSimilarity
isSymmetric() - Method in class elki.similarity.cluster.ClusterIntersectionSimilarity
isSymmetric() - Method in class elki.similarity.cluster.ClusterJaccardSimilarity
isUnpaired() - Method in class elki.evaluation.clustering.pairsegments.Segment: Checks if the segment has a cluster with unpaired objects.
iter - Variable in class elki.clustering.biclustering.AbstractBiclustering: Iterator to use for more efficient random access.
iter - Variable in class elki.clustering.kmeans.KDTreePruningKMeans.Instance: Iterator into the k-d-tree entries.
iter() - Method in class elki.clustering.dbscan.predicates.COPACNeighborPredicate.COPACModel
iter() - Method in class elki.clustering.optics.ClusterOrder: Get an iterator.
iterate(int) - Method in class elki.clustering.kmeans.AbstractKMeans.Instance: Main loop function.
iterate(int) - Method in class elki.clustering.kmeans.CompareMeans.Instance
iterate(int) - Method in class elki.clustering.kmeans.HamerlyKMeans.Instance
iterate(int) - Method in class elki.clustering.kmeans.HartiganWongKMeans.Instance
iterate(int) - Method in class elki.clustering.kmeans.KDTreePruningKMeans.Instance
iterate(int) - Method in class elki.clustering.kmeans.KMeansMinusMinus.Instance
iterate(int) - Method in class elki.clustering.kmeans.KMediansLloyd.Instance
iterate(int) - Method in class elki.clustering.kmeans.LloydKMeans.Instance
iterate(int) - Method in class elki.clustering.kmeans.MacQueenKMeans.Instance
iterate(int) - Method in class elki.clustering.kmeans.SimplifiedElkanKMeans.Instance
iterate(int) - Method in class elki.clustering.kmeans.SingleAssignmentKMeans.Instance
iterate(int) - Method in class elki.clustering.kmeans.spherical.EuclideanSphericalHamerlyKMeans.Instance
iterate(int) - Method in class elki.clustering.kmeans.spherical.EuclideanSphericalSimplifiedElkanKMeans.Instance
iterate(int) - Method in class elki.clustering.kmeans.spherical.SphericalHamerlyKMeans.Instance
iterate(int) - Method in class elki.clustering.kmeans.spherical.SphericalKMeans.Instance
iterate(int) - Method in class elki.clustering.kmeans.spherical.SphericalSimplifiedElkanKMeans.Instance
iterate(int) - Method in class elki.clustering.kmeans.spherical.SphericalSimplifiedHamerlyKMeans.Instance
iterate(int) - Method in class elki.clustering.kmeans.spherical.SphericalSingleAssignmentKMeans.Instance
iterate(int) - Method in class elki.clustering.kmeans.YinYangKMeans.Instance
iterator() - Method in class elki.clustering.optics.OPTICSXi.SteepAreaResult
iterator() - Method in class elki.evaluation.clustering.pairsegments.Segments
iterDBIDs(COPACNeighborPredicate.COPACModel) - Method in class elki.clustering.dbscan.predicates.COPACNeighborPredicate.Instance
iterDBIDs(PreDeConNeighborPredicate.PreDeConModel) - Method in class elki.clustering.dbscan.predicates.FourCNeighborPredicate.Instance
iterDBIDs(PreDeConNeighborPredicate.PreDeConModel) - Method in class elki.clustering.dbscan.predicates.PreDeConNeighborPredicate.Instance
iterDBIDs(DBIDs) - Method in class elki.clustering.dbscan.predicates.ERiCNeighborPredicate.Instance
iterDBIDs(DoubleDBIDList) - Method in class elki.clustering.dbscan.predicates.EpsilonNeighborPredicate.Instance
iterDBIDs(DoubleDBIDList) - Method in class elki.clustering.dbscan.predicates.SimilarityNeighborPredicate.Instance
iterDBIDs(T) - Method in interface elki.clustering.dbscan.predicates.NeighborPredicate.Instance: Add the neighbors to a DBID set
iterToplevelClusters() - Method in class elki.data.Clustering: Iterate over the top level clusters.
itran - Variable in class elki.clustering.kmeans.HartiganWongKMeans.Instance: Updated in quick-transfer
ix - Variable in class elki.clustering.hierarchical.HACAM.Instance: Iterators into the object ids.
ix - Variable in class elki.clustering.hierarchical.MedoidLinkage.Instance: Iterators into the object ids.
ix - Variable in class elki.clustering.hierarchical.MiniMax.Instance: Iterators into the object ids.
iy - Variable in class elki.clustering.hierarchical.HACAM.Instance: Iterators into the object ids.
iy - Variable in class elki.clustering.hierarchical.MedoidLinkage.Instance: Iterators into the object ids.
iy - Variable in class elki.clustering.hierarchical.MiniMax.Instance: Iterators into the object ids.

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