SelvarMix (1.2.1)

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Regularization for Variable Selection in Model-Based Clustering and Discriminant Analysis.

http://cran.r-project.org/web/packages/SelvarMix

Performs a regularization approach to variable selection in the model-based clustering and classification frameworks. First, the variables are arranged in order with a lasso-like procedure. Second, the method of Maugis, Celeux, and Martin-Magniette (2009, 2011) , is adapted to define the role of variables in the two frameworks.

Maintainer: Mohammed Sedki
Author(s): Mohammed Sedki, Gilles Celeux, Cathy Maugis-Rabusseau

License: GPL (>= 3)

Uses: glasso, Rcpp, Rmixmod

Released over 2 years ago.


3 previous versions

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