Python & scikit Learn: replace matrix vector product during training with custom call
In short - no, it is not possible. Mostly because some aritchmetical operations are not even performed in python when you use scikit-learn - they are actually performed by C-based extensions (like libsvm library). You could monkey patch .dot of numpy to do what you want, but you do not have any guarantee that scikit-learn will still work, since it performs some operations using numpy and others using C-extensions.
I've looked through the documentation over at scikit learn and I haven't seen a straightforward way to replace the matrix-vector product evaluations during propagation with a custom evaluation call.
Is there a way to do this that's already part of the API...or are there any tricks that would allow me to inject a custom matrix vector product evaluator?