Dear Max,
Thanks for the reply. I will wait for your further comment
on this.
Regards
Linda Garcia
On Wed, Apr 7, 2010 at 8:03 PM, Max Kuhn <mxk...@gmail.com> wrote:
> Linda,
>
> Thanks for the example.
>
> I did this to make it more reproducible:
>
> set.seed(1)
> X<-matrix(rnorm(50*100),nrow=50)
> y<-rnorm(50*1)
>
> dimnames(X)
>
> colnames(X) <- paste("V", 1:nrow(X))
>
> # Applying caret package
>
> set.seed(2)
> con<-trainControl(method="cv",number=10)
>
> data<-NULL
> data<- train(X,y, "lasso", metric="RMSE",tuneLength = 10, trControl = con)
>
> I see your point here, but this code gives the same results:
>
> fit2 <- enet(X, y, lambda = 0)
> predict(fit2, mode = "fraction", s = data$bestTune$.fraction, type =
> "coefficient")$coef
>
> (at least train() names the predictors).
>
> To me, it looks like enet is doing some filtering:
>
> > dim(X)
> [1] 50 100
> > length(fit2$meanx)
> [1] 56
>
> This appears to be independent of caret. I would contact the package
> maintainer off-list and ask.
>
> Max
>
> ______________________________________________
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> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html<http://www.r-project.org/posting-guide.html>
> and provide commented, minimal, self-contained, reproducible code.
>
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