2013/10/8 Gael Varoquaux <[email protected]>: > On Tue, Oct 08, 2013 at 07:47:40AM +0200, Gilles Louppe wrote: >> Unfortunately, algorithms for recommender systems are not planned in >> scikit-learn in the short or mid-term. > > Indeed in the short term, but are we sure that we want to close the door > to contributions implementing standard approaches for recommender > systems?
+1 for encouraging pull requests that implement recsys building blocks (e.g. matrix factorization) that fit the scikit-learn API (fit and partial_fit + predict or transform) and work with standard input datastructures (e.g. input data is a scipy.sparse matrix or numpy array). We don't want frameworkish code that hard code recsys specific concepts (e.g. users and items) in the API though. -- Olivier Grisel ------------------------------------------------------------------------------ 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=60134071&iu=/4140/ostg.clktrk _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
