On Tue, 27 Nov 2012, Roberto Guidotti wrote: > Well the snippet probabilities = clf.ca.probabilities is only an example > that I've build to reveal the exception (I didn't think is a version > problem, I had 2.0.1 mvpa)!!�
2.0.1 ... hm... I do not remember how life was back then ;) > BTW I was quite sure that the problem relied on the cross validation :)! > �I would like to gather all the predictions/probabilities for each cv > fold. then provide callback to the CrossValidation and there you can collect anything you like from your classifier upon completion of every split. e.g. look at https://github.com/PyMVPA/PyMVPA/blob/HEAD/mvpa2/tests/test_rfe.py#L403 > This why using the ca 'training_stats' during the definition of the > classifier, I had the probabilities of the samples during training? I guess ;) > So I can't have access to every cv fold probabilities/predictions using > CrossValidation object? you can with above mentioned callback > Or I need a manual CrossValidation (and sometimes > a Feature Selection)? if you decide to gather probabilities on both training and testing samples, then you might need indeed manual loop with explicit .train .predict so you get needed probabilities at the right moment. Otherwise -- callback should be sufficient -- Yaroslav O. Halchenko Postdoctoral Fellow, Department of Psychological and Brain Sciences 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 _______________________________________________ Pkg-ExpPsy-PyMVPA mailing list [email protected] http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/pkg-exppsy-pymvpa
