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.

Author
Nema Dean, Adrian E. Raftery, and Luca Scrucca
Date of publication
2015-11-19 17:21:28
Maintainer
Luca Scrucca <luca@stat.unipg.it>
License
GPL (>= 2)
Version
2.2

View on CRAN

Man pages

clustvarsel
Variable Selection for Model-Based Clustering
clustvarsel-internal
Internal 'clustvarsel' functions

Files in this package

clustvarsel
clustvarsel/inst
clustvarsel/inst/CITATION
clustvarsel/inst/NEWS
clustvarsel/NAMESPACE
clustvarsel/R
clustvarsel/R/clvarselgrfwd.R
clustvarsel/R/clvarselgrbkw.R
clustvarsel/R/bicreg.R
clustvarsel/R/startParallel.R
clustvarsel/R/clvarselhlbkw.R
clustvarsel/R/clustvarsel.R
clustvarsel/R/clvarselhlfwd.R
clustvarsel/R/zzz.R
clustvarsel/MD5
clustvarsel/DESCRIPTION
clustvarsel/man
clustvarsel/man/clustvarsel-internal.Rd
clustvarsel/man/clustvarsel.Rd