Misc functions for training and plotting classification and regression models.
Version: | 6.0-73 |
Depends: | R (≥ 2.10), lattice (≥ 0.20), ggplot2 |
Imports: | car, foreach, methods, plyr, ModelMetrics (≥ 1.1.0), nlme, reshape2, stats, stats4, utils, grDevices |
Suggests: | BradleyTerry2, e1071, earth (≥ 2.2-3), fastICA, gam, ipred, kernlab, 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: | 2016-11-10 |
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 |
Reference manual: | caret.pdf |
Vignettes: |
A Short Introduction to the caret Package |
Package source: | caret_6.0-73.tar.gz |
Windows binaries: | r-devel: caret_6.0-73.zip, r-release: caret_6.0-73.zip, r-oldrel: caret_6.0-73.zip |
OS X Mavericks binaries: | r-release: caret_6.0-73.tgz, r-oldrel: caret_6.0-73.tgz |
Old sources: | caret archive |
Reverse depends: | adabag, AntAngioCOOL, conformal, fscaret, hsdar, LncFinder, ordBTL, textmining |
Reverse imports: | aLFQ, arulesCBA, assignPOP, blkbox, caretEnsemble, classifierplots, ContaminatedMixt, crtests, DamiaNN, darch, DecisionCurve, dtwSat, eclust, ensembleR, ESKNN, fitcoach, healthcareai, kernDeepStackNet, kinn, LOGIT, NoiseFiltersR, parboost, PredPsych, preprocomb, preprosim, preproviz, quantable, RStoolbox, specmine, SSL, stepPenal, TLBC, WRTDStidal |
Reverse suggests: | AppliedPredictiveModeling, aVirtualTwins, biomod2, Cubist, data.table, deepboost, discSurv, doParallel, doSNOW, emil, gmum.r, GSIF, idm, Infusion, lulcc, mlr, NeuralNetTools, opera, pdp, ssc, strip, subsemble, SuperLearner |
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