Implementation of gradient functions for pairwise_kernels #25909
denisilie94
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I want to contribute to the sklearn framework by implementing a personal algorithm in the field of large-scale kernel methods. For my current idea, I need an implementation that should provide the gradients/derivatives of the kernel functions with respect to the input vector.
As far as I know the sklearn framework, I see a natural way to implement this functionality in the
pairwise_kernels
function, which should have an additional argumenteval_gradient=False
which should enable the computation of the gradient.Is this a good choice? Or should I think of an independent module that should provide this solution?
I appreciate any help you can provide.
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