Environment for
DeveLoping
KDD-Applications
Supported by Index-Structures

Uses of Class
de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.PROCLUS.PROCLUSCluster

Packages that use PROCLUS.PROCLUSCluster
de.lmu.ifi.dbs.elki.algorithm.clustering.subspace Axis-parallel subspace clustering algorithms The clustering algorithms in this package are instances of both, projected clustering algorithms or subspace clustering algorithms according to the classical but somewhat obsolete classification schema of clustering algorithms for axis-parallel subspaces. 
 

Uses of PROCLUS.PROCLUSCluster in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace
 

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace that return types with arguments of type PROCLUS.PROCLUSCluster
private  Map<Integer,PROCLUS.PROCLUSCluster> PROCLUS.assignPoints(Map<Integer,Set<Integer>> dimensions, Database<V> database)
          Assigns the objects to the clusters.
 

Method parameters in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace with type arguments of type PROCLUS.PROCLUSCluster
private  Set<Integer> PROCLUS.computeBadMedoids(Map<Integer,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(Map<Integer,PROCLUS.PROCLUSCluster> clusters, Map<Integer,Set<Integer>> dimensions, Database<V> database)
          Evaluates the quality of the clusters.
 


Release 0.3 (2010-03-31_1612)