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 <mxkuhn@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
>
> ______________________________________________
> 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<http://www.r-project.org/posting-guide.html>
> and provide commented, minimal, self-contained, reproducible code.
>

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