Package elki.clustering.correlation

Correlation clustering algorithms.

Class Summary

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