2011/11/9 <[email protected]>: > The graph looks very good, good advertising.
Yep, pretty picture ;) > graph_lasso(X,....) takes the data array as an argument, but except > calculating the empirical_covariance at the beginning X is not used > anymore, as far as I could see. > > The algorithm looks very interesting, but I would have cases where I > need to calculate the empirical_covariance myself (e.g. long run > covariance which is a weighted average of covariance and covariance > with lags). > > Would it be possible to use an empirical covariance instead of X as > the main argument, or would you get design inconsistencies? I suppose the cleanest solution would be to just move the guts of the algorithm to a function graph_lasso_from_covariance and call that in graph_lasso. -- Lars Buitinck Scientific programmer, ILPS University of Amsterdam ------------------------------------------------------------------------------ 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
