SelvarClust (Apprentissage)


Variable selection in model-based clustering.

It is devoted to the variable selection in model-based clustering.

 

It is the greedy algorithm associated to the SR modeling proposed by C. Maugis, G. Celeux and M.-L. Martin-Magniette in [1] and [2], modifying the method of Raftery and Dean [3].

 

This software allows to study data where individuals are described by quantitative block variables. It returns a data clustering and the selected model, composed of the number of clusters, the mixture form and the variable partition.


Informations spécifiques
Langage(s) de développement
C++
Langage(s) d'interface
C++
OS supporté


Porteur(s)
Unité
MIA-Paris
Auteur(s)
Maugis, C.
Celeux, G.
Martin-Magniette, M.-L.


 

 

Système d'information scientifique MIA classé par unité (UR, UMR)

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