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.
| Version: |
2.1 |
| Depends: |
R (≥ 2.15), mclust (≥ 4.4), BMA (≥ 3.16), foreach, iterators |
| Suggests: |
MASS, parallel, doParallel |
| Published: |
2014-10-15 |
| Author: |
Nema Dean, Adrian E. Raftery, and Luca Scrucca |
| Maintainer: |
Luca Scrucca <luca at stat.unipg.it> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
no |
| Citation: |
clustvarsel citation info |
| Materials: |
NEWS |
| In views: |
ChemPhys, Cluster, Multivariate |
| CRAN checks: |
clustvarsel results |