Sorry about being unclear.
It is not possible to use another distance in the RBF kernel. You have
to precompute it your own.
But it is possible to do grid search using the precomputed kernel.
Cheers,
Andy
Am 23.05.2012 14:58, schrieb Emeline Landemaine:
I'm not sure to understand: do you mean that this is possible to
change the distance used within the RBF kernel because I didn't see
documentation about it?
Thank you
2012/5/23 Andreas Mueller <[email protected]
<mailto:[email protected]>>
Hi Emeline.
>
> I would like to use SVM in scikit-learn with a RBF kernel
K(x,y)= exp(
> -gamma *d(x,y)^2 ) with d that is not the usual distance but a
> weighted sum of other distances.
> How can I do so? Do I have to precompute the kernel on my own?
Yes, you have to precompute the whole kernel.
> Moreover, to determine gamma, I would like to perform
cross-validation
> on a grid-search but I'm not sure if it's possible with a
precomputed
> kernel ...
>
This is supported at least since 0.11, maybe earlier.
The code is not very mature yet so if you run into any troubles,
please
let us know.
Cheers,
Andy
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