Hi everyone, I am wondering, How can I use external optimization algorithms with scikit-learn, for instance neural network <http://scikit-learn.org/stable/modules/neural_networks_supervised.html#algorithms> , instead of defined algorithms ( Stochastic Gradient Descent, Adam, or L-BFGS).
Furthermore, I want to introduce a new unconstrained optimization algorithm to scikit-learn, implementation of the algorithm and related paper can be found here <https://github.com/sibirbil/PMBSolve>. I couldn't find any explanation <http://scikit-learn.org/stable/developers/contributing.html>, about the situation. Do you have defined procedure to make such kind of contributions? If this is not the case, How should I start to make such a proposal/contribution ? Kind regards, Gürhan C.
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