On 11/08/2011 08:18 PM, Matt Henderson wrote:
So if I have a custom kernel function: CustomKernel(x, y) - I should
do something like:
M = CustomKernel(model.support_vectors_, X)
# if X is a matrix where the rows are test vectors
results = model.predict_proba(M)
Actually, I haven't done this with sklearn yet ;)
But I think that should do it.
?
Is there an example of this somewhere?
Here is an example, but using a python function,
not a gram matrix.:
http://scikit-learn.sourceforge.net/dev/auto_examples/svm/plot_custom_kernel.html#example-svm-plot-custom-kernel-py
And documentation here, though:
http://scikit-learn.sourceforge.net/dev/modules/svm.html#kernel-functions
This definitely needs more documentation. I'll see if I can whip
something up tomorrow.
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