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.
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