Thanks Mathieu, I agree -- a calibration module would be good to have anyways.
I filed an issue on libsvms github account [1] [1] https://github.com/cjlin1/libsvm/issues/13 2014-08-13 3:00 GMT+02:00 Mathieu Blondel <[email protected]>: > sample_weights in scikit-learn comes from a libsvm patch: > http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/#weights_for_data_instances > > So it would seem like probability calibration was omitted from this patch > :-( > > When our calibration module is ready, we could handle the calibration > post-processing ourselves in pure Python. > > Could you report an issue? > > Mathieu > > > On Wed, Aug 13, 2014 at 3:33 AM, Peter Prettenhofer < > [email protected]> wrote: > >> SVC doesnt take class/sample weights into account when calibrating >> probabilities -- this seems to be a bug to me... >> >> >> https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/svm/src/libsvm/svm.cpp#L1895 >> >> best, >> Peter >> >> -- >> Peter Prettenhofer >> >> >> ------------------------------------------------------------------------------ >> >> _______________________________________________ >> Scikit-learn-general mailing list >> [email protected] >> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general >> >> > > > ------------------------------------------------------------------------------ > > _______________________________________________ > Scikit-learn-general mailing list > [email protected] > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > > -- Peter Prettenhofer
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