caret: Classification and Regression Training

Misc functions for training and plotting classification and regression models.

Version: 6.0-64
Depends: R (≥ 2.10), lattice (≥ 0.20), ggplot2
Imports: car, foreach, methods, plyr, nlme, reshape2, stats, stats4, utils, grDevices
Suggests: BradleyTerry2, e1071, earth (≥ 2.2-3), fastICA, gam, ipred, kernlab, klaR, MASS, ellipse, mda, mgcv, mlbench, nnet, party (≥ 0.9-99992), pls, pROC (≥ 1.8), proxy, randomForest, RANN, spls, subselect, pamr, superpc, Cubist, testthat (≥ 0.9.1)
Published: 2016-01-06
Author: Max Kuhn. Contributions from Jed Wing, Steve Weston, Andre Williams, Chris Keefer, Allan Engelhardt, Tony Cooper, Zachary Mayer, Brenton Kenkel, the R Core Team, Michael Benesty, Reynald Lescarbeau, Andrew Ziem, Luca Scrucca, Yuan Tang, and Can Candan.
Maintainer: Max Kuhn <Max.Kuhn at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: NEWS
In views: HighPerformanceComputing, MachineLearning, Multivariate
CRAN checks: caret results


Reference manual: caret.pdf
Vignettes: A Short Introduction to the caret Package
Package source: caret_6.0-64.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Snow Leopard binaries: r-release: caret_6.0-64.tgz, r-oldrel: caret_6.0-47.tgz
OS X Mavericks binaries: r-release: caret_6.0-64.tgz
Old sources: caret archive

Reverse dependencies:

Reverse depends: adabag, conformal, fscaret, hsdar, ordBTL
Reverse imports: aLFQ, caretEnsemble, datafsm, DecisionCurve, ESKNN, LOGIT, parboost, preprocomb, preproviz, RStoolbox, specmine, TLBC
Reverse suggests: AppliedPredictiveModeling, biomod2, Cubist, data.table, deepboost, discSurv, doParallel, doSNOW, emil, gmum.r, kernDeepStackNet, lulcc, mlr, NeuralNetTools, subsemble, SuperLearner