An R package implementing variable selection methodology for Gaussian 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 [aut], Adrian E. Raftery [aut], Luca Scrucca [aut, cre]|
|Date of publication||2017-02-24 16:46:51|
|Maintainer||Luca Scrucca <email@example.com>|
|License||GPL (>= 2)|
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