Correlation clustering algorithms.
Class Summary Class Description CASHThe CASH algorithm is a subspace clustering algorithm based on the Hough transform. CASH.ParParameterization class. COPACCOPAC 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.ParParameterization class. COPAC.SettingsClass to wrap the COPAC settings. ERiCPerforms 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.ParParameterization class. ERiC.SettingsClass to wrap the ERiC settings. FourC4C identifies local subgroups of data objects sharing a uniform correlation. FourC.ParParameterization class. FourC.SettingsClass wrapping the 4C parameter settings. FourC.Settings.ParParameterization class for 4C settings. HiCOImplementation of the HiCO algorithm, an algorithm for detecting hierarchies of correlation clusters. HiCO.ParParameterization class. LMCLUSLinear manifold clustering in high dimensional spaces by stochastic search. LMCLUS.ParParameterization class LMCLUS.SeparationClass to represent a linear manifold separation ORCLUSORCLUS: Arbitrarily ORiented projected CLUSter generation. ORCLUS.ORCLUSClusterEncapsulates the attributes of a cluster. ORCLUS.ParParameterization class. ORCLUS.ProjectedEnergyEncapsulates the projected energy for a cluster.