I don't know if it is faster or better - but the learning rule is insanely simple and it is hard to believe there could be *anything* much faster. It is ten lines - won't copy it here cause the license is longer than the implementation!
Given the connection between PCA and K-means, this implementation (Matlab...) is also related http://homepages.cae.wisc.edu/~ece539/matlab/ghafun.m This points to this paper: http://courses.cs.washington.edu/courses/cse528/09sp/sanger_pca_nn.pdf Basically this is the neural net approach to K-means. I have asked if there is a paper ref - though it might be "too easy" to have a real paper. On Thu, Jun 18, 2015 at 9:58 AM, Andreas Mueller <t3k...@gmail.com> wrote: > > > On 06/18/2015 09:48 AM, Kyle Kastner wrote: > > This link should work http://www.cs.toronto.edu/~rfm/code.html > > <http://www.cs.toronto.edu/%7Erfm/code.html> > Is that faster / better than minibatch k-means? Is there a paper? > > > ------------------------------------------------------------------------------ > _______________________________________________ > Scikit-learn-general mailing list > Scikit-learn-general@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general >
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