It estimates the model for every value of the L1 parameter. See ?predict.enet. When you predict, you have to specify the other parameter (which you can do a variety of ways).
Max On Tue, Aug 25, 2009 at 8:54 AM, Alex Roy<alexroy2...@gmail.com> wrote: > Dear R users, > I am using "enet" package in R for applying "elastic > net" method. In elastic net, two penalities are applied one is lambda1 for > LASSO and lambda2 for ridge ( zou, 2005) penalty. But while running the > analysis, I realised tht, I optimised only one lambda. ( even when I > looked at the example in R, they used only one penality) So, I am wandering > which penalty they are referring to? Is it a combination of penalties or one > of them. I read the paper of zou and hastie but still in doubt. > > Thanks in advance > > Alex > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > 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. > -- Max ______________________________________________ R-help@r-project.org mailing list 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.