On Tue, 27 Nov 2012, Roberto Guidotti wrote: > Dear all, > I've a problem with classifier's conditional attributes (it is possibly > due to a bad command understanding, by myself, I admit!): > clf = LinearCSVMC(C=1, probability=1, enable_ca=['probabilities']) > cvte = CrossValidation(clf, NFoldPartitioner(cvtype = 1), > enable_ca=['stats', 'repetition_results']) > train_err = cvte(evds) > When I try to see inside the conditional attributes of my trained > classifier clf with the command below > probabilities = clf.ca.probabilities
odd enough above snippet (with probabilities = clf.ca.probabilities) works for me just fine. but -- this way you are obtaining probabilities only for the last cross-validation fold. what is the goal -- to get them for every CV fold? (then CrossValidation should get a callback to harvest them) or on all the data (then you would need to "clf.train(evds); clf.predict(evds);" and then gather clf.ca.probabilities > I have this exception > UnknownStateError: Unknown yet value of probabilities > Instead using a classifier defined as: > clf = LinearCSVMC(C=1, probability=1, enable_ca=['probabilities', > 'training_stats']) > I could store my probabilities. > Am I doing all the things well? > Thank you > Roberto -- 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
