Hi all,
Thanks for the help.
1- With rbf functions I do not receive any error but I am not happy of the
obtained result. This is probably just due to my scarce knowledge of SVM
and if someone wants to help me we can continue the discussion here
http://stats.stackexchange.com/questions/115481/one-class-svm-strange-decision-boundary/115510#115510
2 - Regarding the segmentation fault error I do not know the reason for
that.
I have just reported it and I am happy to provide other information
if required.
Thanks a lot,
Luca
>
> I have used it with all kernels and several values of gamma (including the
> default) and never had any issue with it,
>
> Roberto
>
>
> From: Albert Thomas [mailto:[email protected]]
> Sent: Monday, September 15, 2014 10:00 AM
> To: [email protected]
> Subject: Re: [Scikit-learn-general] Bug in one class svm
>
> 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]<mailto:
> [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.
>
>
>
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