I am actually -1 on this, because the consequence would be that np.std(X, axis=-1) would no longer be one. I am afraid that it would confuse the users.
I believe that the n/(n - 1) difference is completely irrelevent for machine learning purpose. If a quantity is relevant, it is the norm of the feature vectors, in the geometrical sens, and thus the current implementation. That said, I am OK adding an additional parameter, if people think that it is important. The one used in numpy, "ddof", is somewhat cryptic, though. ------------------------------------------------------------------------------ LogMeIn Central: Instant, anywhere, Remote PC access and management. Stay in control, update software, and manage PCs from one command center Diagnose problems and improve visibility into emerging IT issues Automate, monitor and manage. Do more in less time with Central http://p.sf.net/sfu/logmein12331_d2d _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general