Hello,
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?
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 ...
Regards,
Emeline
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