On Fri, Feb 15, 2013 at 11:22:02AM +0100, Charles-Pierre Astolfi wrote: > > However, before we do this, I'd like to understand: what is the usecase > > and the purpose for this function? > Which? lars_path or lasso_path or my proposition? > What I propose in an faster and almost (in the sense that it's not > computed via sgd and coefs may vary) drop-in replacement for > lasso_path.
Small remark: lasso_path does a coordinnate descent (CD), and not an SGD. I understand that, but the whole point of lasso_path is to use a CD, and not a LARS, as the CD might be more stable, or even quicker in some situation. SO why do you want such a function? > In fact, some months ago I was trying to do parameter selection for > Lasso using lasso_path and found it quite slow. I understand that. If you want to do parameter selection using Lars, why is LassoLarsCV not well-suited for what you want to do? I still don't understand what usecase you are trying to solve. The following example shows exactly what you are pointing out: http://scikit-learn.org/stable/auto_examples/linear_model/plot_lasso_model_selection.html that Lars is often much faster than CD for a path. G ------------------------------------------------------------------------------ Free Next-Gen Firewall Hardware Offer Buy your Sophos next-gen firewall before the end March 2013 and get the hardware for free! Learn more. http://p.sf.net/sfu/sophos-d2d-feb _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
