Do you have ground-truth? Then you should tune the parameters. Have you done that?
On 08/04/2015 01:45 PM, Ady Wahyudi Paundu wrote: > Hi Andy, thank you for the swift reply. > > No, for both case I was using the same set of parameters (nu and gamma > = 0.01, kernel=rbf) > > Thank you for your suggestion, I will look into it. > > Regards, > Ady > > On 8/5/15, Andreas Mueller <t3k...@gmail.com> wrote: >> Hi Ady. >> Are you selecting parameters separately for the two models in the >> separate case? >> Btw, if you are modelling a single normal, maybe EllipticEnvelope would >> work better. >> >> Best, >> Andy >> >> On 08/04/2015 01:07 PM, Ady Wahyudi Paundu wrote: >>> Hi all, >>> >>> How am I supposed to work with multiple set of normal data for one-class >>> SVM? >>> If I have two normal scenario data set, A and B for learning phase, >>> should I create predictor model separately (M(A) + M(B)) or can I >>> combine A and B to create just a single predictor model (M(A+B))? >>> >>> I have try both approach using one-class SVM in scikit-learn, and my >>> results shows that FPR for combined normal data set is significantly >>> higher (more than 30% in average) than separate prediction (suggesting >>> that separate prediction is better than combined prediction). I just >>> want to confirmed this findings, is that how it supposed to be? >>> >>> Are there any way to improved combined prediction model for one-class >>> SVM? >>> >>> Thank you in advance. >>> >>> Best regards, >>> Ady >>> >>> ------------------------------------------------------------------------------ >>> _______________________________________________ >>> Scikit-learn-general mailing list >>> Scikit-learn-general@lists.sourceforge.net >>> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general >> >> ------------------------------------------------------------------------------ >> _______________________________________________ >> Scikit-learn-general mailing list >> Scikit-learn-general@lists.sourceforge.net >> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general >> > ------------------------------------------------------------------------------ > _______________________________________________ > Scikit-learn-general mailing list > Scikit-learn-general@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general ------------------------------------------------------------------------------ _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
