The algorithm in scikit-learn-extra are usually algorithms which did not meet the inclusion criteria (too early publication, not enough citations, etc.) However, the code quality is as good and tested than scikit-learn (usually they were PR in the main repository). Doing in this manner allows us to find the impact of the algorithms in practice and maybe considering waiving-up the inclusion criterion. On Sat, 2 May 2020 at 06:59, sai_ng <jonpsy101@gmail.com> wrote:

Hey folks ! Hope you're all doing well.

I'm developing Random Fourier Feature implementation in c++ for a repository. Scikits implementation on RBFSampler has been really helpful, and I must say that I'm charmed but how compact, yet powerful each line of code is.

I'm writing this mail because I couldn't find your implementation of Random Binning Features, is it under development?. I tried searching in the issues but, to no avail. I noticed you've put few of your algorithms on a different repository for ex: https://scikit-learn-extra.readthedocs.io/en/latest/generated/sklearn_extra.....

Overall, I'd like to know if it's under development or has there been any draft/proposal or is it already implemented. I'd greatly appreciate if you could point me to other sources (if not here) which have successfully implemented it in code (preferably python/c++)

"Hit me back, Just to chat, Your biggest fan, This is stan" ~ Eminem: Stan

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