When using the rbf kernel, you should try with a gamma > 0. It seems that
you set it to 0.
Albert
2014-09-15 15:37 GMT+02:00 Luca Puggini <[email protected]>:
> Hi,
>
> there is no segmentation fault in the default settings.
> Even if according to the original paper it can make sense to use OCSVM also
> with not rbf kernel.
>
> Maybe there is a bug in the polynomial kernel, I don't know.
>
>
> Despite that also with the RBF kernel I am having some problems with the
> frontier.
>
> I have posted a question with my problem here (plot included)
> http://stats.stackexchange.com/questions/115481/one-class-svm-strange-decision-boundary
>
> I do not exclude that I am doing some mistakes. So please tell me if I am
> wrong.
>
> Thanks a lot,
> Luca
>
>
>
> Hi Luca,
>
> it segfaults?! Can you confirm that it also segfaults if you use the
> default arguments? There is no plot so I cannot say anything about the
> strange decision boundaries.
>
> For my part, I've never used something else than a RBF kernel for a one
> class svm; the RBF kernel has the nice property that all data points lie on
> the surface of a hypersphere and thus the minimum enclosing ball is just
> the hyperplane that separates those points and the origin with the max
> distance to the origin.
>
> 2014-09-15 10:58 GMT+02:00 Luca Puggini <lucapuggio@...>:
>
> >
> > Hi,
> > I am having some problems with the OneClassSVM function.
> >
> > Here you can see my file and the output.
> > http://justpaste.it/h3pw
> >
> > I am sorry but I can not share the used data.
> >
> > I have experienced also other problems like strange decision boundaries.
> >
> > Can someone tell me if I am doing something wrong or if there is a problem
> > in the function?
> >
> > Thanks,
> > Luca
> >
>
>
>
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