caret: Classification and Regression Training

Misc functions for training and plotting classification and regression models.

Version: 6.0-79
Depends: R (≥ 2.10), lattice (≥ 0.20), ggplot2
Imports: foreach, methods, plyr, ModelMetrics (≥ 1.1.0), nlme, reshape2, stats, stats4, utils, grDevices, recipes (≥ 0.0.1), withr (≥ 2.0.0)
Suggests: BradleyTerry2, e1071, earth (≥ 2.2-3), fastICA, gam (≥ 1.15), ipred, kernlab, knitr, klaR, MASS, ellipse, mda, mgcv, mlbench, MLmetrics, nnet, party (≥ 0.9-99992), pls, pROC, proxy, randomForest, RANN, spls, subselect, pamr, superpc, Cubist, testthat (≥ 0.9.1)
Published: 2018-03-29
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, Can Candan, and Tyler Hunt.
Maintainer: Max Kuhn <mxkuhn at gmail.com>
BugReports: https://github.com/topepo/caret/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/topepo/caret/
NeedsCompilation: yes
Materials: NEWS
In views: HighPerformanceComputing, MachineLearning, Multivariate
CRAN checks: caret results

Downloads:

Reference manual: caret.pdf
Vignettes: A Short Introduction to the caret Package
Package source: caret_6.0-79.tar.gz
Windows binaries: r-prerel: caret_6.0-79.zip, r-release: caret_6.0-79.zip, r-oldrel: caret_6.0-79.zip
OS X binaries: r-prerel: caret_6.0-79.tgz, r-release: caret_6.0-79.tgz
Old sources: caret archive

Reverse dependencies:

Reverse depends: adabag, AntAngioCOOL, dtree, fscaret, hsdar, LncFinder, ordBTL, RandPro, textmining
Reverse imports: aLFQ, anomalyDetection, arulesCBA, assignPOP, autoBagging, blkbox, caretEnsemble, CAST, chemmodlab, ck37r, classifierplots, ContaminatedMixt, crtests, cytominer, DamiaNN, datafsm, diceR, dissever, dtwSat, eclust, ensembleR, ESKNN, GPCMlasso, healthcareai, imputeR, kernDeepStackNet, LOGIT, m2b, mcca, MetabolomicsBasics, mosaicModel, neuropsychology, NoiseFiltersR, parboost, PredPsych, predtoolsTS, preprocomb, preprosim, preproviz, quantable, RelimpPCR, rmda, rsMove, RStoolbox, sentometrics, Seurat, SSL, stepPenal, TLBC, TrafficBDE, WRTDStidal
Reverse suggests: AppliedPredictiveModeling, aurelius, aVirtualTwins, biomod2, breakDown, CBDA, Cubist, data.table, deepboost, discSurv, doParallel, doSNOW, emil, FastImputation, forestFloor, GAparsimony, GSIF, idm, iml, iprior, lulcc, mlr, mopa, NeuralNetTools, olsrr, opera, ordinalClust, pdp, recipes, regsem, sparsediscrim, spectacles, ssc, strip, subsemble, SuperLearner
Reverse enhances: prediction

Linking:

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