2013/2/15 Gael Varoquaux <[email protected]>: > On Fri, Feb 15, 2013 at 01:28:43PM +0100, Charles-Pierre Astolfi wrote: >> Just choose the alpha (from a fixed set) that minimizes the RMSE of >> the prediction of the last time step (or the last n time steps with >> exponential decay). Maybe I'm mistaken but there's no easy way to do >> that with LassoLarsCV. > > In my opinion, I am not sure that you want an interpolator that > interpolate the model parameters for specific alphas. You may want to > compute the RMSE at the knots of the path, because I think that this is > where they will be the minimum that you are looking for. > > If for some reason you need to interpolate to specific alphas, it might > be a good strategy to compute the square norm of residuals, and > interpolate this (this square norm will also be linear between the > knots). This is basically the mechanism behind LassoLarsCV. I believe > that something like sklearn.linear_model.least_angle._lars_path_residues > might help you achieve what you want.
I did not know about that. My previous answer is partially wrong then. -- Olivier http://twitter.com/ogrisel - http://github.com/ogrisel ------------------------------------------------------------------------------ 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
