jMEF.BregmanHierarchicalClustering Class Reference

List of all members.

Public Types

enum  LINKAGE_CRITERION { MINIMUM_DISTANCE, MAXIMUM_DISTANCE, AVERAGE_DISTANCE }
 Type of the likage criterion used. More...

Static Public Member Functions

static HierarchicalMixtureModel build (MixtureModel f, Clustering.CLUSTERING_TYPE type, LINKAGE_CRITERION linkage)
 Builds a hierarchical mixture model (class HierarchicalMixtureModel) from an input mixture model and a clustering type.


Detailed Description

Author:
Vincent Garcia

Frank Nielsen

Version:
1.0

License

See file LICENSE.txt

Description

The Bregman hierarchical clustering is the generalization of the hierarchical clustering towards the exponential family. Given a set of weighted distributions (mixture model), the Bregman hierarchical clustering builds a hierarchical mixture model (class HierarchicalMixtureModel). It is then possible from this hierarchical mixture model to

Member Enumeration Documentation

Type of the likage criterion used.

Enumerator:
MINIMUM_DISTANCE 
MAXIMUM_DISTANCE 
AVERAGE_DISTANCE 


Member Function Documentation

static HierarchicalMixtureModel jMEF.BregmanHierarchicalClustering.build ( MixtureModel  f,
Clustering.CLUSTERING_TYPE  type,
LINKAGE_CRITERION  linkage 
) [static]

Builds a hierarchical mixture model (class HierarchicalMixtureModel) from an input mixture model and a clustering type.

Parameters:
f input mixture model given in source parameters
type type of the Bregman divergence used: right-sided, left-sided, or symmetric
linkage linkage criterion used: minimum, maximum, or average distance
Returns:
a hierarchical mixture model


The documentation for this class was generated from the following file:

Generated on Mon Nov 23 15:46:25 2009 for jMEF by  doxygen 1.5.9