Implement weighted feature sampling

It has been reported that feature selection problems with a gigantic number of 
features and only a tiny fraction of relevant features may prove to be 
problematic for RFs, however, which can be remedied by adapting sampling of 
features towards more informative ones. This will make base learners more 
accurate while retaining diversity of learners in the ensembles. See e.g.

http://bioinformatics.oxfordjournals.org/content/24/18/2010.abstract

http://clopinet.com/fextract-book/

for further information.

Original issue reported on code.google.com by timo.erk...@gmail.com on 7 Jan 2012 at 11:37

AnantLabs / rf-ace

Implement weighted feature sampling #13