79 citations · 93 across the 8 of their papers we have counts for
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stat.CO2017
Variable selection in model-based clustering and discriminant analysis with a regularization approach
Gilles Celeux, Cathy Maugis-Rabusseau, Mohammed Sedki
Relevant methods of variable selection have been proposed in model-based clustering and classification. These methods are making use of backward or forward procedures to define the…
stat.CO2017★ 6 cited
Variable selection for mixed data clustering: a model-based approach
Matthieu Marbac, Mohammed Sedki
We propose two approaches for selecting variables in latent class analysis (i.e.,mixture model assuming within component independence), which is the common model-based clustering m…