See: Description
Class | Description |
---|---|
CASH |
Provides the CASH algorithm, an subspace clustering algorithm based on the
Hough transform.
|
CASH.Parameterizer |
Parameterization class.
|
COPAC<V extends NumberVector<V,?>,D extends Distance<D>> |
Provides the COPAC algorithm, 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<V,?>,D extends Distance<D>> |
Parameterization class.
|
ERiC<V extends NumberVector<V,?>> |
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<V,?>> |
Parameterization class.
|
FourC<V extends NumberVector<V,?>> |
4C identifies local subgroups of data objects sharing a uniform correlation.
|
FourC.Parameterizer<O extends NumberVector<O,?>> |
Parameterization class.
|
HiCO<V extends NumberVector<V,?>> |
Implementation of the HiCO algorithm, an algorithm for detecting hierarchies
of correlation clusters.
|
HiCO.Parameterizer<V extends NumberVector<V,?>> |
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<V,?>> |
ORCLUS provides the ORCLUS algorithm, an algorithm to find clusters in high
dimensional spaces.
|
ORCLUS.Parameterizer<V extends NumberVector<V,?>> |
Parameterization class.
|
Correlation clustering algorithms