Hi, I have been working recently with the factor analysis implementation in scikit-learn and checked it against its main reference (algorithm 21 in David Barber’s book). I noticed there is a difference from the algorithm described in the book in the way the SVD results are used. In the book, SVD is performed for the scaled data matrix like this: X = USV’, and then the first N columns in U and first N elements in S are used to compute the factors in each iteration (N being the number of components in the model). However, in scikit-learn code, the first N rows in V’ (or first N columns in V) are used instead. Is there any specific reason for using V instead of U in this case?
Best regards, João ------------------------------------------------------------------------------ Download BIRT iHub F-Type - The Free Enterprise-Grade BIRT Server from Actuate! Instantly Supercharge Your Business Reports and Dashboards with Interactivity, Sharing, Native Excel Exports, App Integration & more Get technology previously reserved for billion-dollar corporations, FREE http://pubads.g.doubleclick.net/gampad/clk?id=164703151&iu=/4140/ostg.clktrk _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
