clustvarsel: Variable Selection for Model-Based Clustering

A function which implements variable selection methodology for model-based clustering which allows to find the (locally) optimal subset of variables in a data set that have group/cluster information. A greedy or headlong search can be used, either in a forward-backward or backward-forward direction, with or without sub-sampling at the hierarchical clustering stage for starting MCLUST models. By default the algorithm uses a sequential search, but parallelisation is also available.

AuthorNema Dean, Adrian E. Raftery, and Luca Scrucca
Date of publication2015-11-19 17:21:28
MaintainerLuca Scrucca <luca@stat.unipg.it>
LicenseGPL (>= 2)
Version2.2

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Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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