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.
|Author||Nema Dean, Adrian E. Raftery, and Luca Scrucca|
|Date of publication||2015-11-19 17:21:28|
|Maintainer||Luca Scrucca <email@example.com>|
|License||GPL (>= 2)|