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.
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