Howdy This question and the one right after in the FAQ are probably relevant re: inclusion of new algorithms: http://scikit-learn.org/stable/faq.html#what-are-the-inclusion-criteria-for-new-algorithms. The gist is that we only include well established algorithms, and there are no end to those. I think it is unlikely that a PR will get merged with a cutting edge new algorithm, as the scope of scikit-learn isn't necessary "the latest" as opposed to "the classics." You may also consider writing a scikit-contrib package that basically creates what you're interested in in scikit-learn format, but external to the project. We'd be more than happy to link to it. If the algorithm becomes a smashing success over time, we'd reconsider adding it to the main code base.
As to your first question, you should check out how the current optimizers are written for the algorithm you're interested in. I don't think there's a plug and play way to drop in your own optimizer like many deep learning packages support, unfortunately. You'd probably have to modify the code directly to support your own. Let me know if you have any other questions. Jacob On Mon, Jul 10, 2017 at 7:58 AM, Gürhan Ceylan <grhancey...@gmail.com> wrote: > 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. > > > _______________________________________________ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn > >
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
