caret: Classification and Regression Training

Misc functions for training and plotting classification and regression models.

Version: 6.0-93
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: 2022-08-09
Author: Max Kuhn ORCID iD [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
CRAN checks: caret results

Documentation:

Reference manual: caret.pdf
Vignettes: A Short Introduction to the caret Package

Downloads:

Package source: caret_6.0-93.tar.gz
Windows binaries: r-devel: caret_6.0-93.zip, r-release: caret_6.0-93.zip, r-oldrel: caret_6.0-93.zip
macOS binaries: r-release (arm64): caret_6.0-93.tgz, r-oldrel (arm64): caret_6.0-93.tgz, r-release (x86_64): caret_6.0-93.tgz, r-oldrel (x86_64): caret_6.0-93.tgz
Old sources: caret archive

Reverse dependencies:

Reverse depends: adabag, AntAngioCOOL, AutoStepwiseGLM, branchpointer, dbcsp, fscaret, GWAS.BAYES, hsdar, iForecast, JQL, manymodelr, maPredictDSC, MLSeq, MobileTrigger, MRReg, MSclassifR, natstrat, RandPro, SpatialML
Reverse imports: AdaSampling, aLFQ, ampir, animalcules, assignPOP, autoBagging, biomod2, BLRShiny, BLRShiny2, bnviewer, caretEnsemble, caretForecast, CAST, chemmodlab, ChIC, ChIC.data, classifierplots, ClinicalUtilityRecal, clustDRM, CMShiny, coca, CondiS, ConfusionTableR, ContaminatedMixt, CopulaCenR, criticality, crtests, CSCNet, CTShiny, CTShiny2, CytoGLMM, cytominer, D2MCS, DamiaNN, DaMiRseq, datafsm, dissever, DMLLZU, DMTL, driveR, dtwSat, eclust, Ecume, ensembleR, EpiSemble, fairness, fdm2id, FeatureTerminatoR, featuretoolsR, FFTrees, fieldRS, fmf, foster, FSinR, FuncNN, glmdisc, glmtrans, glmtree, GPCMlasso, healthcareai, HPiP, hypervolume, icardaFIGSr, iSFun, KCSKNNShiny, KCSNBShiny, kfa, KNNShiny, KnowSeq, l1spectral, LassoGEE, LDLcalc, lilikoi, LncFinder, LOGANTree, LPRelevance, m2b, MAI, MAIT, mand, mcca, metabCombiner, MetabolomicsBasics, metaEnsembleR, microbiomeMarker, MiDA, mikropml, MiMIR, mistyR, MLDataR, mlmts, mlquantify, MNLR, modelgrid, mosaicModel, MRFcov, MSiP, MSstatsSampleSize, multiclassPairs, multiSight, mxnorm, NBShiny, NBShiny2, NBShiny3, nbTransmission, NEONiso, nestedcv, NeuralSens, NNS, nonet, NonProbEst, npcs, OddsPlotty, omu, oncrawlR, OOS, panelWranglR, ParallelDSM, pathwayTMB, PDATK, Pi, POMA, pomodoro, preciseTAD, PredPsych, predtoolsTS, PriceIndices, pRoloc, promor, RadialVisGadgets, RaSEn, refitME, RelimpPCR, REMP, RISCA, rmda, robustcov, RStoolbox, Rtropical, SAEforest, sandwichr, scAnnotatR, scGPS, sentometrics, shinyr, SLEMI, soilassessment, SPONGE, sregsurvey, ssr, stabiliser, stepPenal, studyStrap, SubCellBarCode, supersigs, swag, TCGAbiolinksGUI, theft, TrafficBDE, transcriptR, TSGS, varEst, waterquality, waves, WRTDStidal
Reverse suggests: AppliedPredictiveModeling, archetyper, aVirtualTwins, breakDown, broom, butcher, cat2cat, CBDA, cellity, ciu, condvis2, deepboost, discSurv, DNAshapeR, doParallel, doSNOW, dynfeature, easyalluvial, ENMTools, EventDetectR, FastImputation, FCBF, flashlight, GAparsimony, genefu, ibawds, idm, iml, imputeR, iprior, latrend, LKT, lulcc, metaforest, metamicrobiomeR, MLInterfaces, mlr, mlr3filters, mlr3spatiotempcv, mmb, modelplotr, moreparty, mshap, NeuralNetTools, NHSRdatasets, opera, ordinalClust, pdp, Platypus, pmml, posterior, pre, predfairness, purgeR, r2pmml, randomForestSRC, regsem, rScudo, SAMtool, shapr, sits, SLOPE, SmartMeterAnalytics, spectacles, spFSR, ssc, SSLR, strip, subsemble, SuperLearner, superml, SurvMetrics, TBSignatureProfiler, tornado, vetiver, vip
Reverse enhances: bestglm, prediction

Linking:

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