On a related note, any thoughts on how to tame a dataset where I have 20 samples and 3 million features?
P On Wed, Mar 30, 2011 at 11:57 PM, Per B. Sederberg <[email protected]> wrote: > On Wed, Mar 30, 2011 at 11:44 PM, Yaroslav Halchenko > <[email protected]> wrote: >> >> On Wed, 30 Mar 2011, Per B. Sederberg wrote: >>> clfr = GLMNET_R(alpha=.5, model_type='naive', enable_ca=['estimates']) >> >> so it is a regression. Wrap with RegressionAsClassifier to gain >> classification ;) >> >> thus metrics for regressions: >> >>> -------> print(sclf.ca.stats) >>> Statistics Mean Std Min Max >>> ---------- ----- ----- ----- ----- >>> Data: >>> RMP_t 2.285 0.696 1.3 4 >>> STD_t 0 0 0 0 >>> >...< >> > > I actually want the regression and not the classifier, but I now > totally understand the stats printout. I was confused because the CCe > is 1 minus the correlation. > >>> Also, I really just want to get the predictions/estimates of the >>> classifier from each fold, but I don't know how to get that out. >> >> those, since you have stats, are also available within >> sclf.ca.stats.sets >> > > Awesome! Yes, I had just found that and the exact keys I needed were: > > cv.ca.stats.stats['RMP_p_all'] > cv.ca.stats.stats['RMP_t_all'] > > Now I think I'm all set! > > Thanks, > P > > >> -- >> =------------------------------------------------------------------= >> Keep in touch www.onerussian.com >> Yaroslav Halchenko www.ohloh.net/accounts/yarikoptic >> >> _______________________________________________ >> Pkg-ExpPsy-PyMVPA mailing list >> [email protected] >> http://lists.alioth.debian.org/mailman/listinfo/pkg-exppsy-pymvpa >> > _______________________________________________ Pkg-ExpPsy-PyMVPA mailing list [email protected] http://lists.alioth.debian.org/mailman/listinfo/pkg-exppsy-pymvpa
