Folks, this is my first message on this newsgroup, so first: Hi!
I have two questions, I hope they are not too trivial: 1. Access to coefficients in LassoCV I use LassoCV to find the optimal alpha for my problem. For analysis purposes I'd like to get access to the paths coefficients, more or less like it's done in this old example here: http://scikit-learn.org/0.8/auto_examples/linear_model/plot_lasso_path_crossval.html I see that the coef_path_ attribute has been removed from lassoCV. What's the rationale behind this choice? To get the coefficients, should I use lasso_path and find the best MSE by myself, or did I miss something obvious here? 2. Convergence warnings My use case with Lasso is a "small n (48) large p (~100)" problem with some predictors highly collinear. I constantly get the following warning message when using LassoCV: "ConvergenceWarning: Objective did not converge. You might want to increase the number of iteration" Since the results look fine and LassoCV was able to find a MSE minimun, I guess that one (or more) of the models along the path had trouble to converge. I tried increasing iterations and tolerance thresholds without success. What should I do to solve this problem without awkward try-and-error steps? Which particular feature in my data could cause this warning? Thanks a lot! Fabien ------------------------------------------------------------------------------ Slashdot TV. Videos for Nerds. Stuff that Matters. http://pubads.g.doubleclick.net/gampad/clk?id=160591471&iu=/4140/ostg.clktrk _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
