On Wed, Nov 09, 2011 at 11:43:40PM +0100, bthirion wrote: > > What do people think? Should I:
> > 1. change graph_lasso to take the empirical covariance as an input > > 2. add an 'X_is_cov' parameter to the estimators > +1 for the second one. I actually was suggesting both, and 1 as a mean for 2. > If we want to introduce some kind of automated guess of the > regularization parameter, we'll have to know the dimension I believe ? You mean the number of samples? Actually, no, what is important is the number of degrees of freedom (I know that you know this). Things like the OAS try to estimate it from the covariance matrix. G ------------------------------------------------------------------------------ RSA(R) Conference 2012 Save $700 by Nov 18 Register now http://p.sf.net/sfu/rsa-sfdev2dev1 _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
