Package de.lmu.ifi.dbs.elki.algorithm.clustering.correlation

Correlation clustering algorithms


Class Summary
CASH Provides the CASH algorithm, an subspace clustering algorithm based on the hough transform.
CASH.Parameterizer Parameterization class.
COPAC<V extends NumberVector<V,?>,D extends Distance<D>> Provides the COPAC algorithm, an algorithm to partition a database according to the correlation dimension of its objects and to then perform an arbitrary clustering algorithm over the partitions.
COPAC.Parameterizer<V extends NumberVector<V,?>,D extends Distance<D>> Parameterization class.
ERiC<V extends NumberVector<V,?>> Performs correlation clustering on the data partitioned according to local correlation dimensionality and builds a hierarchy of correlation clusters that allows multiple inheritance from the clustering result.
ERiC.Parameterizer<V extends NumberVector<V,?>> Parameterization class.
FourC<V extends NumberVector<V,?>> 4C identifies local subgroups of data objects sharing a uniform correlation.
FourC.Parameterizer<O extends NumberVector<O,?>> Parameterization class.
HiCO<V extends NumberVector<V,?>> Implementation of the HiCO algorithm, an algorithm for detecting hierarchies of correlation clusters.
HiCO.Parameterizer<V extends NumberVector<V,?>> Parameterization class.
ORCLUS<V extends NumberVector<V,?>> ORCLUS provides the ORCLUS algorithm, an algorithm to find clusters in high dimensional spaces.
ORCLUS.Parameterizer<V extends NumberVector<V,?>> Parameterization class.

Package de.lmu.ifi.dbs.elki.algorithm.clustering.correlation Description

Correlation clustering algorithms

Release 0.4.0 (2011-09-20_1324)