I haven't looked closely, but is Barber's data format considered to be
examples as columns, or examples as rows? That difference is usually what I
see in a bunch of different SVD based algorithms. It is very annoying when
reading the literature.
aka.
what Michael said
On Fri, Dec 5, 2014 at 10:24 AM, João Felipe Santos <joao....@gmail.com>
wrote:
> 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
>
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