> Is there a way to extract MSE for a lambda, e.g. lambda.1se? nevermind this specific question. it's now obvious. However my overall question stands.
On Fri, Sep 16, 2016 at 10:10 AM, Dominik Schneider < dominik.schnei...@colorado.edu> wrote: > I'm doing some linear modeling and am new to the ridge/lasso/elasticnet > procedures. In my case I have N>>p (p=15 based on variables used in past > literature and some physical reasoning) so my understanding is that I > should be interested in ridge regression to avoid the issue of > multicollinearity of predictors. Lasso is useful when p>>N. > > In the past I have performed step-wise regression with stepAIC in both > directions to choose my variables and then used VIF to determine if any of > these variables are correlated. My understanding is that ridge regression > is a more robust approach for this workflow. > > Reading the glmnet_beta vignette, it describes the alpha parameter where > alpha=1 is a lasso regression and alpha=0 is a ridge regression. Farther > down the authors suggest a 10 fold validation to determine an alpha value > and based on the plots shown, say that alpha=1 does the best here. However, > all the models look like they approach the same MSE and alpha=0 is the > lowest curve for all lambda (but maybe this second point doesn't matter?). > With my data I get a very similar looking set of curves so I'm trying to > decide if I should stick with alpha=1 instead of alpha=0. Is there a way to > extract MSE for a lambda, e.g. lambda.1se? > > Any advice or clarification is appreciated. Thanks. > Dominik > > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.