[pymvpa] Individual measures for subjects

[Yaroslav Halchenko]

On Fri, 31 Jan 2014, Arman Eshaghi wrote:

>    and would it be possible to get predicted probabilities instead of just
>    labeled predictions? Something similar to 'predict_prob' �from SVS in
>    scikit-learn?

well -- for SVM those are just 'estimates' of probabilities since SVM do
not deal with probabilities per se.  You could enable/collect them from
a SVMs .ca.probabilities via enable_ca=['probabilities'].  For other
classifiers, e.g. SMLR, they would really be probabilities it relies
upon to make a decision, thus accessible from 'estimates' ca.

you could pass those .ca into resultant datasets collected by
CrossValidation by specifying to your classifier

pass_attr=['ca.probabilities']

but this is not yet present in released version :-/ "we are working on
it" (i.e. on next releaase)

-- 
Yaroslav O. Halchenko, Ph.D.
http://neuro.debian.net http://www.pymvpa.org http://www.fail2ban.org
Senior Research Associate,     Psychological and Brain Sciences Dept.
Dartmouth College, 419 Moore Hall, Hinman Box 6207, Hanover, NH 03755
Phone: +1 (603) 646-9834                       Fax: +1 (603) 646-1419
WWW:   http://www.linkedin.com/in/yarik