Uses of Class
elki.data.Cluster
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Packages that use Cluster Package Description elki.clustering.biclustering Biclustering algorithms.elki.clustering.correlation Correlation clustering algorithms.elki.clustering.hierarchical.extraction Extraction of partitional clusterings from hierarchical results.elki.clustering.kmeans K-means clustering and variations.elki.clustering.kmeans.initialization Initialization strategies for k-means.elki.clustering.kmeans.quality Quality measures for k-Means results.elki.clustering.optics OPTICS family of clustering algorithms.elki.clustering.subspace Axis-parallel subspace clustering algorithms.elki.data Basic classes for different data types, database object types and label types.elki.evaluation.clustering Evaluation of clustering results.elki.evaluation.clustering.internal Internal evaluation measures for clusterings.elki.evaluation.clustering.pairsegments Pair-segment analysis of multiple clusterings.elki.outlier.clustering Clustering based outlier detection.elki.result Result types, representation and handling.elki.result.textwriter Text serialization (CSV, Gnuplot, Console, ...).elki.result.textwriter.naming Naming schemes for clusters (for output when an algorithm does not generate cluster names).elki.similarity.cluster Similarity measures for comparing clusters.elki.visualization.style Style management for ELKI visualizations.elki.visualization.visualizers.optics Visualizers that do work on OPTICS plots.elki.visualization.visualizers.scatterplot.cluster Visualizers for clustering results based on 2D projections.elki.visualization.visualizers.visunproj Visualizers that do not use a particular projection. -
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Uses of Cluster in elki.clustering.biclustering
Methods in elki.clustering.biclustering that return Cluster Modifier and Type Method Description protected Cluster<BiclusterModel>
AbstractBiclustering. defineBicluster(long[] rows, long[] cols)
Defines a Bicluster as given by the included rows and columns.protected Cluster<BiclusterModel>
AbstractBiclustering. defineBicluster(java.util.BitSet rows, java.util.BitSet cols)
Defines a Bicluster as given by the included rows and columns. -
Uses of Cluster in elki.clustering.correlation
Methods in elki.clustering.correlation that return types with arguments of type Cluster Modifier and Type Method Description private java.util.List<java.util.List<Cluster<CorrelationModel>>>
ERiC. extractCorrelationClusters(Clustering<Model> dbscanResult, Relation<? extends NumberVector> relation, int dimensionality, ERiCNeighborPredicate.Instance npred)
Extracts the correlation clusters and noise from the copac result and returns a mapping of correlation dimension to maps of clusters within this correlation dimension.Methods in elki.clustering.correlation with parameters of type Cluster Modifier and Type Method Description private boolean
ERiC. isParent(ERiCNeighborPredicate.Instance npred, Cluster<CorrelationModel> parent, It<Cluster<CorrelationModel>> iter)
Returns true, if the specified parent cluster is a parent of one child of the children clusters.Method parameters in elki.clustering.correlation with type arguments of type Cluster Modifier and Type Method Description private void
ERiC. buildHierarchy(Clustering<CorrelationModel> clustering, java.util.List<java.util.List<Cluster<CorrelationModel>>> clusterMap, ERiCNeighborPredicate.Instance npred)
private boolean
ERiC. isParent(ERiCNeighborPredicate.Instance npred, Cluster<CorrelationModel> parent, It<Cluster<CorrelationModel>> iter)
Returns true, if the specified parent cluster is a parent of one child of the children clusters. -
Uses of Cluster in elki.clustering.hierarchical.extraction
Fields in elki.clustering.hierarchical.extraction with type parameters of type Cluster Modifier and Type Field Description protected java.util.Collection<Cluster<DendrogramModel>>
SimplifiedHierarchyExtraction.TempCluster. children
(Finished) child clustersMethods in elki.clustering.hierarchical.extraction that return Cluster Modifier and Type Method Description protected Cluster<DendrogramModel>
AbstractCutDendrogram.Instance. makeCluster(int seq, DBIDs members)
Make the cluster for the given objectprotected Cluster<DendrogramModel>
SimplifiedHierarchyExtraction.Instance. makeCluster(int seq, double depth, DBIDs members)
Make the cluster for the given objectprotected Cluster<DendrogramModel>
SimplifiedHierarchyExtraction.Instance. toCluster(SimplifiedHierarchyExtraction.TempCluster temp, Clustering<DendrogramModel> clustering)
Make the cluster for the given objectMethods in elki.clustering.hierarchical.extraction with parameters of type Cluster Modifier and Type Method Description void
SimplifiedHierarchyExtraction.TempCluster. addChild(Cluster<DendrogramModel> clu)
Add a child cluster.private double
HDBSCANHierarchyExtraction.Instance. collectChildren(HDBSCANHierarchyExtraction.TempCluster temp, Clustering<DendrogramModel> clustering, WritableDoubleDataStore glosh, HDBSCANHierarchyExtraction.TempCluster cur, Cluster<DendrogramModel> clus, boolean flatten)
Recursive flattening of clusters.private double
HDBSCANHierarchyExtraction.Instance. finalizeCluster(HDBSCANHierarchyExtraction.TempCluster temp, Clustering<DendrogramModel> clustering, WritableDoubleDataStore glosh, Cluster<DendrogramModel> parent, boolean flatten)
Make the cluster for the given object -
Uses of Cluster in elki.clustering.kmeans
Methods in elki.clustering.kmeans that return types with arguments of type Cluster Modifier and Type Method Description protected java.util.List<Cluster<M>>
GMeans. splitCluster(Cluster<M> parentCluster, Relation<V> relation)
protected java.util.List<Cluster<M>>
XMeans. splitCluster(Cluster<M> parentCluster, Relation<V> relation)
Conditionally splits the clusters based on the information criterion.Methods in elki.clustering.kmeans with parameters of type Cluster Modifier and Type Method Description protected double[][]
GMeans. splitCentroid(Cluster<? extends MeanModel> parentCluster, Relation<V> relation)
protected double[][]
XMeans. splitCentroid(Cluster<? extends MeanModel> parentCluster, Relation<V> relation)
Split an existing centroid into two initial centers.protected java.util.List<Cluster<M>>
GMeans. splitCluster(Cluster<M> parentCluster, Relation<V> relation)
protected java.util.List<Cluster<M>>
XMeans. splitCluster(Cluster<M> parentCluster, Relation<V> relation)
Conditionally splits the clusters based on the information criterion. -
Uses of Cluster in elki.clustering.kmeans.initialization
Method parameters in elki.clustering.kmeans.initialization with type arguments of type Cluster Modifier and Type Method Description void
Predefined. setInitialClusters(java.util.List<? extends Cluster<? extends MeanModel>> initialMeans)
Set the initial means. -
Uses of Cluster in elki.clustering.kmeans.quality
Methods in elki.clustering.kmeans.quality with parameters of type Cluster Modifier and Type Method Description static double
AbstractKMeansQualityMeasure. varianceContributionOfCluster(Cluster<? extends MeanModel> cluster, NumberVectorDistance<?> distance, Relation<? extends NumberVector> relation)
Variance contribution of a single cluster. -
Uses of Cluster in elki.clustering.optics
Fields in elki.clustering.optics with type parameters of type Cluster Modifier and Type Field Description (package private) java.util.HashSet<Cluster<OPTICSModel>>
OPTICSXi.ClusterHierarchyBuilder. curclusters
Current "unattached" clusters. -
Uses of Cluster in elki.clustering.subspace
Methods in elki.clustering.subspace that return Cluster Modifier and Type Method Description protected Cluster<SubspaceModel>
DOC. makeCluster(Relation<? extends NumberVector> relation, DBIDs C, long[] D)
Utility method to create a subspace cluster from a list of DBIDs and the relevant attributes.protected Cluster<SubspaceModel>
DOC. runDOC(Relation<? extends NumberVector> relation, ArrayModifiableDBIDs S, int d, int n, int m, int r, int minClusterSize)
Performs a single run of DOC, finding a single cluster.protected Cluster<SubspaceModel>
FastDOC. runDOC(Relation<? extends NumberVector> relation, ArrayModifiableDBIDs S, int d, int n, int m, int r, int minClusterSize)
Performs a single run of FastDOC, finding a single cluster.Methods in elki.clustering.subspace that return types with arguments of type Cluster Modifier and Type Method Description private java.util.List<Cluster<Model>>
SUBCLU. runDBSCAN(Relation<V> relation, DBIDs ids, Subspace subspace)
Runs the DBSCAN algorithm on the specified partition of the database in the given subspace.private java.util.List<Cluster<SubspaceModel>>
DiSH. sortClusters(Relation<? extends NumberVector> relation, it.unimi.dsi.fastutil.objects.Object2ObjectMap<long[],java.util.List<ArrayModifiableDBIDs>> clustersMap)
Returns a sorted list of the clusters w.r.t. the subspace dimensionality in descending order.Methods in elki.clustering.subspace with parameters of type Cluster Modifier and Type Method Description private boolean
DiSH. isParent(Relation<? extends NumberVector> relation, Cluster<SubspaceModel> parent, It<Cluster<SubspaceModel>> iter, int db_dim)
Returns true, if the specified parent cluster is a parent of one child of the children clusters.Method parameters in elki.clustering.subspace with type arguments of type Cluster Modifier and Type Method Description private Subspace
SUBCLU. bestSubspace(java.util.List<Subspace> subspaces, Subspace candidate, java.util.TreeMap<Subspace,java.util.List<Cluster<Model>>> clusterMap)
Determines thed
-dimensional subspace of the(d+1)
-dimensional candidate with minimal number of objects in the cluster.private void
DiSH. buildHierarchy(Relation<? extends NumberVector> database, Clustering<SubspaceModel> clustering, java.util.List<Cluster<SubspaceModel>> clusters, int dimensionality)
Builds the cluster hierarchy.private boolean
DiSH. isParent(Relation<? extends NumberVector> relation, Cluster<SubspaceModel> parent, It<Cluster<SubspaceModel>> iter, int db_dim)
Returns true, if the specified parent cluster is a parent of one child of the children clusters. -
Uses of Cluster in elki.data
Fields in elki.data with type parameters of type Cluster Modifier and Type Field Description static java.util.Comparator<Cluster<?>>
Cluster. BY_NAME_SORTER
A partial comparator for Clusters, based on their name.private ModifiableHierarchy<Cluster<M>>
Clustering. hierarchy
Cluster hierarchy.private java.util.List<Cluster<M>>
Clustering. toplevelclusters
Keep a list of top level clusters.Methods in elki.data that return types with arguments of type Cluster Modifier and Type Method Description java.util.List<Cluster<M>>
Clustering. getAllClusters()
Collect all clusters (recursively) into a List.Hierarchy<Cluster<M>>
Clustering. getClusterHierarchy()
Get the cluster hierarchy.java.util.List<Cluster<M>>
Clustering. getToplevelClusters()
Return top level clustersIt<Cluster<M>>
Clustering. iterToplevelClusters()
Iterate over the top level clusters.Methods in elki.data with parameters of type Cluster Modifier and Type Method Description void
Clustering. addChildCluster(Cluster<M> parent, Cluster<M> child)
Add a cluster to the clustering.void
Clustering. addToplevelCluster(Cluster<M> clus)
Add a cluster to the clustering.Constructor parameters in elki.data with type arguments of type Cluster Constructor Description Clustering(java.util.List<Cluster<M>> toplevelclusters)
Constructor with a list of top level clusters -
Uses of Cluster in elki.evaluation.clustering
Methods in elki.evaluation.clustering with parameters of type Cluster Modifier and Type Method Description static double
EvaluateClustering. evaluateRanking(ScoreEvaluation eval, Cluster<?> clus, DoubleDBIDList ranking)
Evaluate given a cluster (of positive elements) and a scoring list. -
Uses of Cluster in elki.evaluation.clustering.internal
Methods in elki.evaluation.clustering.internal with parameters of type Cluster Modifier and Type Method Description protected double
CIndex. processCluster(Cluster<?> cluster, java.util.List<? extends Cluster<?>> clusters, int i, DistanceQuery<O> dq, DoubleHeap maxDists, DoubleHeap minDists, int w)
protected void
CIndex. processSingleton(Cluster<?> cluster, Relation<? extends O> rel, DistanceQuery<O> dq, DoubleHeap maxDists, DoubleHeap minDists, int w)
Method parameters in elki.evaluation.clustering.internal with type arguments of type Cluster Modifier and Type Method Description static int
SimplifiedSilhouette. centroids(Relation<? extends NumberVector> rel, java.util.List<? extends Cluster<?>> clusters, NumberVector[] centroids, NoiseHandling noiseOption)
Compute centroids.protected double[]
ConcordantPairsGammaTau. computeWithinDistances(Relation<? extends NumberVector> rel, java.util.List<? extends Cluster<?>> clusters, int withinPairs)
static int
VarianceRatioCriterion. globalCentroid(Centroid overallCentroid, Relation<? extends NumberVector> rel, java.util.List<? extends Cluster<?>> clusters, NumberVector[] centroids, NoiseHandling noiseOption)
Update the global centroid.protected double
CIndex. processCluster(Cluster<?> cluster, java.util.List<? extends Cluster<?>> clusters, int i, DistanceQuery<O> dq, DoubleHeap maxDists, DoubleHeap minDists, int w)
double[]
DaviesBouldinIndex. withinGroupDistances(Relation<? extends NumberVector> rel, java.util.List<? extends Cluster<?>> clusters, NumberVector[] centroids)
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Uses of Cluster in elki.evaluation.clustering.pairsegments
Fields in elki.evaluation.clustering.pairsegments with type parameters of type Cluster Modifier and Type Field Description private java.util.List<java.util.List<? extends Cluster<?>>>
Segments. clusters
ClustersMethod parameters in elki.evaluation.clustering.pairsegments with type arguments of type Cluster Modifier and Type Method Description private void
Segments. recursivelyFill(java.util.List<java.util.List<? extends Cluster<?>>> cs)
private void
Segments. recursivelyFill(java.util.List<java.util.List<? extends Cluster<?>>> cs, int depth, SetDBIDs first, SetDBIDs second, int[] path, boolean objectsegment)
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Uses of Cluster in elki.outlier.clustering
Methods in elki.outlier.clustering with parameters of type Cluster Modifier and Type Method Description private double
CBLOF. computeLargeClusterCBLOF(O obj, NumberVectorDistance<? super O> distance, NumberVector clusterMean, Cluster<MeanModel> cluster)
private double
CBLOF. computeSmallClusterCBLOF(O obj, NumberVectorDistance<? super O> distance, java.util.List<NumberVector> largeClusterMeans, Cluster<MeanModel> cluster)
Method parameters in elki.outlier.clustering with type arguments of type Cluster Modifier and Type Method Description private void
CBLOF. computeCBLOFs(Relation<O> relation, WritableDoubleDataStore cblofs, DoubleMinMax cblofMinMax, java.util.List<? extends Cluster<MeanModel>> largeClusters, java.util.List<? extends Cluster<MeanModel>> smallClusters)
Compute the CBLOF scores for all the data.private int
CBLOF. getClusterBoundary(Relation<O> relation, java.util.List<? extends Cluster<MeanModel>> clusters)
Compute the boundary index separating the large cluster from the small cluster. -
Uses of Cluster in elki.result
Methods in elki.result with parameters of type Cluster Modifier and Type Method Description private DoubleObjPair<Polygon>
KMLOutputHandler. buildHullsRecursively(Cluster<Model> clu, Hierarchy<Cluster<Model>> hier, java.util.Map<java.lang.Object,DoubleObjPair<Polygon>> hulls, Relation<? extends NumberVector> coords)
Recursively step through the clusters to build the hulls.private java.lang.StringBuilder
KMLOutputHandler. makeDescription(Cluster<?> c)
Make an HTML description.Method parameters in elki.result with type arguments of type Cluster Modifier and Type Method Description private DoubleObjPair<Polygon>
KMLOutputHandler. buildHullsRecursively(Cluster<Model> clu, Hierarchy<Cluster<Model>> hier, java.util.Map<java.lang.Object,DoubleObjPair<Polygon>> hulls, Relation<? extends NumberVector> coords)
Recursively step through the clusters to build the hulls. -
Uses of Cluster in elki.result.textwriter
Methods in elki.result.textwriter with parameters of type Cluster Modifier and Type Method Description private void
TextWriter. writeClusterResult(Database db, StreamFactory streamOpener, Clustering<Model> clustering, Cluster<Model> clus, java.util.List<Relation<?>> ra, NamingScheme naming)
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Uses of Cluster in elki.result.textwriter.naming
Fields in elki.result.textwriter.naming with type parameters of type Cluster Modifier and Type Field Description private java.util.Map<Cluster<?>,java.lang.String>
SimpleEnumeratingScheme. names
Assigned cluster names.Methods in elki.result.textwriter.naming with parameters of type Cluster Modifier and Type Method Description java.lang.String
NamingScheme. getNameFor(Cluster<?> cluster)
Retrieve a name for the given cluster.java.lang.String
SimpleEnumeratingScheme. getNameFor(Cluster<?> cluster)
Retrieve the cluster name. -
Uses of Cluster in elki.similarity.cluster
Methods in elki.similarity.cluster with type parameters of type Cluster Modifier and Type Method Description <T extends Cluster<?>>
DistanceSimilarityQuery<T>ClusterIntersectionSimilarity. instantiate(Relation<T> relation)
<T extends Cluster<?>>
DistanceSimilarityQuery<T>ClusterJaccardSimilarity. instantiate(Relation<T> relation)
Methods in elki.similarity.cluster that return types with arguments of type Cluster Modifier and Type Method Description SimpleTypeInformation<? super Cluster<?>>
ClusterIntersectionSimilarity. getInputTypeRestriction()
SimpleTypeInformation<? super Cluster<?>>
ClusterJaccardSimilarity. getInputTypeRestriction()
Methods in elki.similarity.cluster with parameters of type Cluster Modifier and Type Method Description double
ClusterIntersectionSimilarity. distance(Cluster<?> o1, Cluster<?> o2)
double
ClusterJaccardSimilarity. distance(Cluster<?> o1, Cluster<?> o2)
double
ClusterIntersectionSimilarity. similarity(Cluster<?> o1, Cluster<?> o2)
double
ClusterJaccardSimilarity. similarity(Cluster<?> o1, Cluster<?> o2)
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Uses of Cluster in elki.visualization.style
Fields in elki.visualization.style with type parameters of type Cluster Modifier and Type Field Description (package private) it.unimi.dsi.fastutil.objects.Object2IntOpenHashMap<Cluster<?>>
ClusterStylingPolicy. cmap
Map from cluster objects to color offsets.Methods in elki.visualization.style with parameters of type Cluster Modifier and Type Method Description int
ClusterStylingPolicy. getStyleForCluster(Cluster<?> c)
Get the style number for a cluster. -
Uses of Cluster in elki.visualization.visualizers.optics
Method parameters in elki.visualization.visualizers.optics with type arguments of type Cluster Modifier and Type Method Description private void
OPTICSClusterVisualization.Instance. drawClusters(Clustering<OPTICSModel> clustering, It<Cluster<OPTICSModel>> clusters, int depth, java.util.Map<Cluster<?>,java.lang.String> colormap)
Recursively draw clustersprivate void
OPTICSClusterVisualization.Instance. drawClusters(Clustering<OPTICSModel> clustering, It<Cluster<OPTICSModel>> clusters, int depth, java.util.Map<Cluster<?>,java.lang.String> colormap)
Recursively draw clusters -
Uses of Cluster in elki.visualization.visualizers.scatterplot.cluster
Methods in elki.visualization.visualizers.scatterplot.cluster with parameters of type Cluster Modifier and Type Method Description private double
ClusterAlphaHullVisualization.Instance. addRecursively(java.util.ArrayList<double[]> hull, Hierarchy<Cluster<Model>> hier, Cluster<Model> clus)
Recursively add a cluster and its children for alpha shapes.private DoubleObjPair<Polygon>
ClusterConvexHullVisualization.Instance. buildHullsRecursively(Cluster<Model> clu, Hierarchy<Cluster<Model>> hier, java.util.Map<java.lang.Object,DoubleObjPair<Polygon>> hulls)
Recursively step through the clusters to build the hulls.Method parameters in elki.visualization.visualizers.scatterplot.cluster with type arguments of type Cluster Modifier and Type Method Description private double
ClusterAlphaHullVisualization.Instance. addRecursively(java.util.ArrayList<double[]> hull, Hierarchy<Cluster<Model>> hier, Cluster<Model> clus)
Recursively add a cluster and its children for alpha shapes.private DoubleObjPair<Polygon>
ClusterConvexHullVisualization.Instance. buildHullsRecursively(Cluster<Model> clu, Hierarchy<Cluster<Model>> hier, java.util.Map<java.lang.Object,DoubleObjPair<Polygon>> hulls)
Recursively step through the clusters to build the hulls. -
Uses of Cluster in elki.visualization.visualizers.visunproj
Methods in elki.visualization.visualizers.visunproj with parameters of type Cluster Modifier and Type Method Description private double
KeyVisualization.Instance. drawHierarchy(SVGPlot svgp, MarkerLibrary ml, DoubleDoublePair size, DoubleDoublePair pos, int depth, Cluster<Model> cluster, it.unimi.dsi.fastutil.objects.Object2IntOpenHashMap<Cluster<Model>> cnum, Hierarchy<Cluster<Model>> hier)
private static <M extends Model>
voidKeyVisualization. findDepth(Hierarchy<Cluster<M>> hier, Cluster<M> cluster, int[] size)
Recursive depth computation.Method parameters in elki.visualization.visualizers.visunproj with type arguments of type Cluster Modifier and Type Method Description private double
KeyVisualization.Instance. drawHierarchy(SVGPlot svgp, MarkerLibrary ml, DoubleDoublePair size, DoubleDoublePair pos, int depth, Cluster<Model> cluster, it.unimi.dsi.fastutil.objects.Object2IntOpenHashMap<Cluster<Model>> cnum, Hierarchy<Cluster<Model>> hier)
private double
KeyVisualization.Instance. drawHierarchy(SVGPlot svgp, MarkerLibrary ml, DoubleDoublePair size, DoubleDoublePair pos, int depth, Cluster<Model> cluster, it.unimi.dsi.fastutil.objects.Object2IntOpenHashMap<Cluster<Model>> cnum, Hierarchy<Cluster<Model>> hier)
private static <M extends Model>
voidKeyVisualization. findDepth(Hierarchy<Cluster<M>> hier, Cluster<M> cluster, int[] size)
Recursive depth computation.
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