Updating the singular value decomposition


10-Jan-2018 00:37

The basic of this update are dictated by the Sherman-Morrison formula.. \begin A^* = A - UV^T \end the Woodbury formula comes into play.For this package to work only Numpy, Scipy and Matplotlib are required. However, Scipy need to be compiled from sources in order to use some LAPACK function "dlasd4" which are not exposed originally.

They have chosen mean squared error as the measure of accuracy, which means if you guess 1.5 and the actual rating was 2, you get docked for (2-1.5)^2 points, or 0.25.

Cholesky updates exists (' Ditch' the recommender literature then and focus on image processing.



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