Package 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.

See: Description

Interface Summary

Interface	Description
SubspaceClusteringAlgorithm<M extends SubspaceModel>	Interface for subspace clustering algorithms that use a model derived from SubspaceModel, that can then be post-processed for outlier detection.

Class Summary

Class	Description
CLIQUE	Implementation of the CLIQUE algorithm, a grid-based algorithm to identify dense clusters in subspaces of maximum dimensionality.
CLIQUE.Parameterizer	Parameterization class.
DiSH<V extends NumberVector>	Algorithm for detecting subspace hierarchies.
DiSH.DiSHClusterOrder	DiSH cluster order.
DiSH.Parameterizer<V extends NumberVector>	Parameterization class.
DOC<V extends NumberVector>	DOC is a sampling based subspace clustering algorithm.
DOC.Parameterizer<V extends NumberVector>	Parameterization class.
FastDOC<V extends NumberVector>	The heuristic variant of the DOC algorithm, FastDOC Reference: C.
FastDOC.Parameterizer<V extends NumberVector>	Parameterization class.
HiSC<V extends NumberVector>	Implementation of the HiSC algorithm, an algorithm for detecting hierarchies of subspace clusters.
HiSC.Parameterizer<V extends NumberVector>	Parameterization class.
P3C<V extends NumberVector>	P3C: A Robust Projected Clustering Algorithm.
P3C.ClusterCandidate	This class is used to represent potential clusters.
P3C.Parameterizer<V extends NumberVector>	Parameterization class.
P3C.Signature	P3C Cluster signature.
PreDeCon<V extends NumberVector>	PreDeCon computes clusters of subspace preference weighted connected points.
PreDeCon.Parameterizer<V extends NumberVector>	Parameterization class.
PreDeCon.Settings	Class containing all the PreDeCon settings.
PreDeCon.Settings.Parameterizer	Parameterization class.
PROCLUS<V extends NumberVector>	The PROCLUS algorithm, an algorithm to find subspace clusters in high dimensional spaces.
PROCLUS.DoubleIntInt	Simple triple.
PROCLUS.Parameterizer<V extends NumberVector>	Parameterization class.
PROCLUS.PROCLUSCluster	Encapsulates the attributes of a cluster.
SUBCLU<V extends NumberVector>	Implementation of the SUBCLU algorithm, an algorithm to detect arbitrarily shaped and positioned clusters in subspaces.
SUBCLU.Parameterizer<V extends NumberVector>	Parameterization class.

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

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.