On Mon, Jun 02, 2014 at 12:27:34AM +0100, Luca Puggini wrote: > This is a good alternative to SVD and it is much faster in situations where we > have a lot of variables and we are interested only in a small number of > components. > This is a well known and tested algorithm and I was actually surprised when I > discovered that it is not in sklearn. (Maybe it has been replaced by a faster > alternative?)
It is in scikit-learn, I believe, but written in such a way that nobody finds it are uses it (there are a few lessons to be learned there :) ): inside sklearn.cross_decomposition, you'll find some NIPALS. G ------------------------------------------------------------------------------ Learn Graph Databases - Download FREE O'Reilly Book "Graph Databases" is the definitive new guide to graph databases and their applications. Written by three acclaimed leaders in the field, this first edition is now available. Download your free book today! http://p.sf.net/sfu/NeoTech _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
