clustvarsel (version 2.1)
Variable Selection for Model-Based Clustering
Description
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 parallelization is also available.