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
Langage(s) d'interface
OS supporté

Maugis, C.
Celeux, G.
Martin-Magniette, M.-L.



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