[R-pkgs] New versions of the caret (3.08) and caretLSF (1.12) packages

[Kuhn, Max]

New versions of the caret (3.08) and caretLSF (1.12) packages have been
released. 

caret (short for "Classification And REgression Training") aims to
simplify the model building process. The package has functions for data
splitting, pre-processing and model tuning, as well as other
miscellaneous functions. 

In the new versions:

   - The elasticnet and the lasso (from the enet package) have been
added

   - mars and fda models are now fit using the earth package. Instead of
using nk as a tuning parameter, these models now use the default nk from
the training set and tunes over nprune. This mimics the process used by
earth/mars/fda more closely.

   - A bug was fixed with leave-one-out cross-validation.

   - For some models, the calculations in the train function are much
more efficient. Wherever possible, caret tries to avoid re-fitting
models if it can get predictions from sub-models. For example, an object
for a boosted tree with 500 trees can often be used to get predictions
for any boosted tree with less than 500 trees. The affected models are:
pls, plsda, earth, rpart, gbm, gamboost, glmboost, blackboost, ctree,
pam, enet and lasso.


The caretLSF package is a parallel processing version of caret. The
other caret package, caretNWS, will be updated to work with the new
version of caret shortly.

Please email me at max dot kuhn at pfizer dot com with any questions or
comments

Max