Class Summary |
ByLabelClustering<O extends DatabaseObject> |
Pseudo clustering using labels. |
ByLabelHierarchicalClustering<O extends DatabaseObject> |
Pseudo clustering using labels. |
DBSCAN<O extends DatabaseObject,D extends Distance<D>> |
DBSCAN provides the DBSCAN algorithm,
an algorithm to find density-connected sets in a database. |
DeLiClu<O extends NumberVector<O,?>,D extends Distance<D>> |
DeLiClu provides the DeLiClu algorithm, a hierarchical algorithm to find density-connected sets in a database. |
EM<V extends RealVector<V,?>> |
Provides the EM algorithm (clustering by expectation maximization). |
KMeans<D extends Distance<D>,V extends RealVector<V,?>> |
Provides the k-means algorithm. |
OPTICS<O extends DatabaseObject,D extends Distance<D>> |
OPTICS provides the OPTICS algorithm. |
ProjectedDBSCAN<V extends RealVector<V,?>> |
Provides an abstract algorithm requiring a VarianceAnalysisPreprocessor. |
SLINK<O extends DatabaseObject,D extends Distance<D>> |
Efficient implementation of the Single-Link Algorithm SLINK of R. |
SNNClustering<O extends DatabaseObject,D extends Distance<D>> |
Shared nearest neighbor clustering. |
TrivialAllInOne<O extends DatabaseObject> |
Trivial pseudo-clustering that just considers all points to be one big cluster. |
TrivialAllNoise<O extends DatabaseObject> |
Trivial pseudo-clustering that just considers all points to be noise. |