prediction intervals with caret

Question

I've been using the caret package in R to run some boosted regression tree and random forest models and am hoping to generate prediction intervals for a set of new cases using the inbuilt cross-validation routine.

The trainControl function allows you to save the hold-out predictions at each of the n-folds, but I'm wondering whether unknown cases can also be predicted at each fold using the built-in functions, or whether I need to use a separate loop to build the models n-times.

Any advice much appreciated

Answer 1

Check the R package quantregForest, available at CRAN. It can easily calculate prediction intervals for random forest models. There's a nice paper by the author of the package, explaining the backgrounds of the method. (Sorry, I can't say anything about prediction intervals for BRT models; I'm looking for them by myself...)