The caret package (short for Classification And REgression Training) is a set of functions that attempt to streamline the process for creating predictive models. The package contains tools for:

  • data splitting
  • pre-processing
  • feature selection
  • model tuning using resampling
  • variable importance estimation

as well as other functionality.

These package documentation pages are now hosted on guthub. R-Forge help pages should automatically forward but, if they don't, please let me know.

There are many different modeling functions in R. Some have different syntax for model training and/or prediction. The package started off as a way to provide a uniform interface the functions themselves, as well as a way to standardize common tasks (such parameter tuning and variable importance).

Shameless promotion! I have a book out called Applied Predictive Modeling which features caret and over 40 other R packages. It is on sale at Amazon or the the publisher's website. There is a companion website too.

There is also a paper on caret in the Journal of Statistical Software. The example data can be obtained here (the predictors) and here (the outcomes).

The current release version can be found on CRAN.

You can always email me with questions, comments or suggestions.