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

Correlation clustering algorithms

See: Description

Class Summary

Class	Description
CASH<V extends NumberVector>	The CASH algorithm is a subspace clustering algorithm based on the Hough transform.
CASH.Parameterizer	Parameterization class.
COPAC<V extends NumberVector>	COPAC is 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>	Parameterization class.
COPAC.Settings	Class to wrap the COPAC settings.
COPAC.Settings.Parameterizer	Parameterization class.
ERiC<V extends NumberVector>	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>	Parameterization class.
ERiC.Settings	Class to wrap the ERiC settings.
ERiC.Settings.Parameterizer	Parameterization class.
FourC<V extends NumberVector>	4C identifies local subgroups of data objects sharing a uniform correlation.
FourC.Parameterizer<O extends NumberVector>	Parameterization class.
FourC.Settings	Class wrapping the 4C parameter settings.
FourC.Settings.Parameterizer	Parameterization class for 4C settings.
HiCO<V extends NumberVector>	Implementation of the HiCO algorithm, an algorithm for detecting hierarchies of correlation clusters.
HiCO.Parameterizer<V extends NumberVector>	Parameterization class.
LMCLUS	Linear manifold clustering in high dimensional spaces by stochastic search.
LMCLUS.Parameterizer	Parameterization class
LMCLUS.Separation	Class to represent a linear manifold separation
ORCLUS<V extends NumberVector>	ORCLUS: Arbitrarily ORiented projected CLUSter generation.
ORCLUS.Parameterizer<V extends NumberVector>	Parameterization class.

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

Correlation clustering algorithms