Uses of Class
elki.clustering.subspace.PROCLUS.PROCLUSCluster

Packages that use PROCLUS.PROCLUSCluster

Package	Description
elki.clustering.subspace	Axis-parallel subspace clustering algorithms.

Uses of PROCLUS.PROCLUSCluster in elki.clustering.subspace

Methods in elki.clustering.subspace that return types with arguments of type PROCLUS.PROCLUSCluster

Modifier and Type	Method	Description
private java.util.ArrayList<PROCLUS.PROCLUSCluster>	PROCLUS.assignPoints(elki.database.ids.ArrayDBIDs m_current, long[][] dimensions, elki.database.relation.Relation<? extends elki.data.NumberVector> database)	Assigns the objects to the clusters.
private java.util.List<PROCLUS.PROCLUSCluster>	PROCLUS.finalAssignment(java.util.List<elki.utilities.pairs.Pair<double[],long[]>> dimensions, elki.database.relation.Relation<? extends elki.data.NumberVector> database)	Refinement step to assign the objects to the final clusters.

Method parameters in elki.clustering.subspace with type arguments of type PROCLUS.PROCLUSCluster

Modifier and Type	Method	Description
private elki.database.ids.DBIDs	PROCLUS.computeBadMedoids(elki.database.ids.ArrayDBIDs m_current, java.util.ArrayList<PROCLUS.PROCLUSCluster> clusters, int threshold)	Computes the bad medoids, where the medoid of a cluster with less than the specified threshold of objects is bad.
private double	PROCLUS.evaluateClusters(java.util.ArrayList<PROCLUS.PROCLUSCluster> clusters, long[][] dimensions, elki.database.relation.Relation<? extends elki.data.NumberVector> database)	Evaluates the quality of the clusters.
private java.util.List<elki.utilities.pairs.Pair<double[],long[]>>	PROCLUS.findDimensions(java.util.ArrayList<PROCLUS.PROCLUSCluster> clusters, elki.database.relation.Relation<? extends elki.data.NumberVector> database)	Refinement step that determines the set of correlated dimensions for each cluster centroid.