clustvarsel (2.2)

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.

Maintainer: Luca Scrucca
Author(s): Nema Dean, Adrian E. Raftery, and Luca Scrucca

License: GPL (>= 2)

Uses: BMA, foreach, iterators, mclust, MASS, doParallel

Released over 2 years ago.