Hello devs, I'm a final year computer engineering student, currently doing my masters and engineering degree in recommender systems.
Last summer, after an optimization course, I found a quite interesting recognition algorithm called : Artificial immune recognition system (described in the paper below), and I was wondering if its implementation would be interesting for the scikit-learn library. I wrote a first version of it which is available in my GitHub page ( https://github.com/AghilesAzzoug/Artificial-Immune-System <http://s.bl-1.com/h/ctT3Hlzb?url=https://github.com/AghilesAzzoug/Artificial-Immune-System>), the code is only working for Iris datasets (since it was only a test). I'm happy to get any suggestions of critics from the community. Sincerely, Aghiles Paper ref. : Watkins, A., Timmis, J., & Boggess, L. (2004). Artificial immune recognition system (AIRS): An immune-inspired supervised learning algorithm. *Genetic Programming and Evolvable Machines*, *5*(3), 291-317.
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