Hi Taylor. Thanks for wanting to contribute. I am a bit ambivalent wrt to adding SOMs.
I have not seen or heard of an application where SOMs work better than any of the clustering or manifold-learning algorithms in sklearn. On the other hand, it is a classical algorithm and having a reference implementation would be kind of nice. Also they are in ESL. Do you have any application where they work better than other algorithms in sklearn? There was a PR of a SOM somewhere. It looks like it got closed because it was inactive for too long (~2 years?). What variant did you implement? I think we should stay at pretty vanilla and I guess a 2d grid for the neurons would suffice, as this is by far the most common variation. Cheers, Andy PS: I really really dislike SOMs. Don't let that discourage you ;) On 10/21/2013 10:41 PM, Taylor Sather wrote: > Hello, > > I was wondering if there was any effort to implement a Kohonen map in > scikit-learn? I'm thinking of getting my implementation up to snuff for a > pull request, but I wanted to ask the mailing list before I invested too much > effort. > > > Thanks, > Taylor Sather > ------------------------------------------------------------------------------ > October Webinars: Code for Performance > Free Intel webinars can help you accelerate application performance. > Explore tips for MPI, OpenMP, advanced profiling, and more. Get the most from > the latest Intel processors and coprocessors. See abstracts and register > > http://pubads.g.doubleclick.net/gampad/clk?id=60135991&iu=/4140/ostg.clktrk > _______________________________________________ > Scikit-learn-general mailing list > Scikit-learn-general@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general ------------------------------------------------------------------------------ October Webinars: Code for Performance Free Intel webinars can help you accelerate application performance. Explore tips for MPI, OpenMP, advanced profiling, and more. Get the most from the latest Intel processors and coprocessors. See abstracts and register > http://pubads.g.doubleclick.net/gampad/clk?id=60135991&iu=/4140/ostg.clktrk _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
