scikit-learn/scikit-learn — Issue #454: mclust for gmm
Author: jovo
Created: 2011-12-05 17:54:45+00:00
State: open

MCLUST (http://www.stat.washington.edu/mclust/) is the standard package for mixture modeling in the stats world. essentially, it is doing model based clustering as described in Fraley and Raftery, 2002 (www.stat.washington.edu/raftery/Research/PDF/fraley2002.pdf). this means gaussian mixture modeling, essentially. it has a number of choices for regularizing the covariance matrix. it then uses BIC to choose. the current implementation of gmm in sklearn has several of these options (full, diag, tied, spherical), but that is only about half the options in MCLUST. and then while i see BIC is implemented for LassoLars, it seems to be tied to that.

so, i wonder whether there are plans to:
1) update gmm.py to include other versions of covariance regularization
2) update model selection to include BIC generally (i couldn't find the src for the BIC implementation, so i can't tell how BIC is implemented now).

if no plans exist, i might fork. PyMix has some model selection using BIC (http://pymix.org/docu/mixture-pysrc.html#modelSelection), so some of that code could be borrowed.....

thanks all for building such useful stuff!