A nice idea would be to extend the scipy NNLS in the ways needed to use it in scikit-learn's NMF instead of the _nls_subproblem code translated from C.J. Lin's code.
The scipy NNLS is written in Fortran. I'd like to bench _nls_subproblem against it. Maybe we could have a cython projected sgd non-negative least square method with L1 constraints that would support sparse data as well? We discussed this idea before, but would it be an NNLS solver? Would this lead to a sparse NMF? Vlad On Feb 3, 2012, at 11:32 , Mathieu Blondel wrote: > For non-negative least-squares, you can use this: > > http://docs.scipy.org/doc/scipy-0.7.x/reference/generated/scipy.optimize.nnls.html > > We could also add an estimator that implements fit and predict in > scikit-learn (although the above function doesn't support sparse > matrices :$) > > Mathieu > > ------------------------------------------------------------------------------ > Try before you buy = See our experts in action! > The most comprehensive online learning library for Microsoft developers > is just $99.99! Visual Studio, SharePoint, SQL - plus HTML5, CSS3, MVC3, > Metro Style Apps, more. Free future releases when you subscribe now! > http://p.sf.net/sfu/learndevnow-dev2 > _______________________________________________ > Scikit-learn-general mailing list > [email protected] > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general ------------------------------------------------------------------------------ Try before you buy = See our experts in action! The most comprehensive online learning library for Microsoft developers is just $99.99! Visual Studio, SharePoint, SQL - plus HTML5, CSS3, MVC3, Metro Style Apps, more. Free future releases when you subscribe now! http://p.sf.net/sfu/learndevnow-dev2 _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
