See: Description
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 | Description |
---|---|
CLIQUE<V extends NumberVector<?>> |
Implementation of the CLIQUE algorithm, a grid-based algorithm to identify
dense clusters in subspaces of maximum dimensionality.
|
CLIQUE.Parameterizer<V extends NumberVector<?>> |
Parameterization class.
|
DiSH<V extends NumberVector<?>> |
Algorithm for detecting subspace hierarchies.
|
DiSH.Parameterizer<V extends NumberVector<?>> |
Parameterization class.
|
DOC<V extends NumberVector<?>> |
Provides the DOC algorithm, and it's heuristic variant, FastDOC.
|
DOC.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.
|
PROCLUS<V extends NumberVector<?>> |
Provides the PROCLUS algorithm, an algorithm to find subspace clusters in
high dimensional spaces.
|
PROCLUS.Parameterizer<V extends NumberVector<?>> |
Parameterization class.
|
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.
|
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.