caret: Classification and Regression Training

Misc functions for training and plotting classification and regression models.

Version: 6.0-90
Depends: ggplot2, lattice (≥ 0.20), R (≥ 3.2.0)
Imports: e1071, foreach, grDevices, methods, ModelMetrics (≥ 1.2.2.2), nlme, plyr, pROC, recipes (≥ 0.1.10), reshape2, stats, stats4, utils, withr (≥ 2.0.0)
Suggests: BradleyTerry2, covr, Cubist, dplyr, earth (≥ 2.2-3), ellipse, fastICA, gam (≥ 1.15), ipred, kernlab, klaR, knitr, MASS, Matrix, mda, mgcv, mlbench, MLmetrics, nnet, pamr, party (≥ 0.9-99992), pls, proxy, randomForest, RANN, rmarkdown, rpart, spls, subselect, superpc, testthat (≥ 0.9.1), themis (≥ 0.1.3)
Published: 2021-10-09
Author: Max Kuhn [aut, cre], Jed Wing [ctb], Steve Weston [ctb], Andre Williams [ctb], Chris Keefer [ctb], Allan Engelhardt [ctb], Tony Cooper [ctb], Zachary Mayer [ctb], Brenton Kenkel [ctb], R Core Team [ctb], Michael Benesty [ctb], Reynald Lescarbeau [ctb], Andrew Ziem [ctb], Luca Scrucca [ctb], Yuan Tang [ctb], Can Candan [ctb], Tyler Hunt [ctb]
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_6.0-90.tar.gz
Windows binaries: r-devel: caret_6.0-90.zip, r-devel-UCRT: caret_6.0-90.zip, r-release: caret_6.0-90.zip, r-oldrel: caret_6.0-89.zip
macOS binaries: r-release (arm64): caret_6.0-89.tgz, r-release (x86_64): caret_6.0-90.tgz, r-oldrel: caret_6.0-90.tgz
Old sources: caret archive

Reverse dependencies:

Reverse depends: adabag, AntAngioCOOL, AutoStepwiseGLM, branchpointer, dtree, fscaret, GWAS.BAYES, hsdar, iForecast, JQL, manymodelr, maPredictDSC, MLSeq, MobileTrigger, MRReg, natstrat, RandPro, SQB
Reverse imports: AdaSampling, aLFQ, ampir, animalcules, assignPOP, autoBagging, biomod2, BLRShiny, BLRShiny2, bnviewer, caretEnsemble, CAST, cat2cat, chemmodlab, ChIC, ChIC.data, classifierplots, ClinicalUtilityRecal, clustDRM, CMShiny, coca, ConfusionTableR, ContaminatedMixt, CopulaCenR, crtests, CSUV, CTShiny, CTShiny2, CytoGLMM, cytominer, D2MCS, DamiaNN, DaMiRseq, datafsm, dbcsp, dissever, DMLLZU, DMTL, driveR, dtwSat, eclust, Ecume, ensembleR, fairness, fdm2id, FeatureTerminatoR, featuretoolsR, fieldRS, fmf, foster, FSinR, FuncNN, fusionchartsR, glmdisc, glmtrans, glmtree, GPCMlasso, healthcareai, icardaFIGSr, iSFun, JFE, KCSKNNShiny, KCSNBShiny, KNNShiny, KnowSeq, LassoGEE, latrend, LDLcalc, lilikoi, LKT, LncFinder, LPRelevance, m2b, MAIT, mand, mcca, metabCombiner, MetabolomicsBasics, MetaClean, metaEnsembleR, MiDA, mikropml, mistyR, MLDAShiny, MLDAShiny2, mlquantify, MNLR, modelgrid, mosaicModel, MRFcov, MSiP, MSstatsSampleSize, multiclassPairs, multiSight, NBShiny, NBShiny2, NBShiny3, nbTransmission, NeuralSens, NNS, NoiseFiltersR, nonet, NonProbEst, OddsPlotty, oncrawlR, OOS, panelWranglR, ParallelDSM, parboost, pathwayTMB, PDATK, Pi, POMA, preciseTAD, PredPsych, predtoolsTS, PriceIndices, pRoloc, quantable, RadialVisGadgets, RaSEn, refitME, RelimpPCR, REMP, RISCA, rmda, robustcov, RStoolbox, scClassifR, scGPS, sentometrics, SLEMI, smartR, soilassessment, specmine, sregsurvey, ssr, stabiliser, stepPenal, studyStrap, SubCellBarCode, supersigs, swag, TCGAbiolinksGUI, TestDimorph, TIGERr, transcriptR, TSGS, varEst, waterquality, waves, WRTDStidal
Reverse suggests: AppliedPredictiveModeling, archetyper, aurelius, aVirtualTwins, breakDown, broom, butcher, CBDA, cellity, ciu, condvis2, deepboost, discSurv, DNAshapeR, doParallel, doSNOW, dynfeature, easyalluvial, ENMTools, EventDetectR, FCBF, flashlight, GAparsimony, genefu, ibawds, idm, iml, imputeR, iprior, lulcc, metaforest, metamicrobiomeR, MLInterfaces, mlr, mlr3filters, mlr3spatiotempcv, mmb, modelplotr, moreparty, mshap, NeuralNetTools, NHSRdatasets, opera, ordinalClust, pdp, pmml, posterior, predfairness, purgeR, r2pmml, randomForestSRC, regsem, RGCxGC, rScudo, SAMtool, shapr, SLOPE, SmartMeterAnalytics, spectacles, spFSR, ssc, SSLR, strip, SuperLearner, superml, SurvMetrics, TBSignatureProfiler, varrank, vip, xspliner
Reverse enhances: bestglm, prediction

Linking:

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