Uses of Class
elki.data.Cluster

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.

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 clusters

Methods 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 object
protected Cluster<DendrogramModel>	SimplifiedHierarchyExtraction.Instance.makeCluster(int seq, double depth, DBIDs members)	Make the cluster for the given object
protected Cluster<DendrogramModel>	SimplifiedHierarchyExtraction.Instance.toCluster(SimplifiedHierarchyExtraction.TempCluster temp, Clustering<DendrogramModel> clustering)	Make the cluster for the given object

Methods 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 the d-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 clusters
It<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)

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	Clusters

Method 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)

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)

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)

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 clusters
private 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> void	KeyVisualization.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> void	KeyVisualization.findDepth(Hierarchy<Cluster<M>> hier, Cluster<M> cluster, int[] size)	Recursive depth computation.