Misc functions for training and plotting classification and
regression models.
| Version: |
6.0-86 |
| Depends: |
R (≥ 3.2.0), lattice (≥ 0.20), ggplot2 |
| Imports: |
foreach, methods, plyr, ModelMetrics (≥ 1.2.2.2), nlme, reshape2, stats, stats4, utils, grDevices, recipes (≥ 0.1.10), withr (≥ 2.0.0), pROC |
| 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, proxy, randomForest, RANN, spls, subselect, pamr, superpc, Cubist, testthat (≥ 0.9.1), rpart, dplyr, covr |
| Published: |
2020-03-20 |
| 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 |
| Reverse depends: |
adabag, AntAngioCOOL, AutoStepwiseGLM, branchpointer, dtree, fscaret, GWAS.BAYES, hsdar, iForecast, JQL, manymodelr, maPredictDSC, MLSeq, MobileTrigger, MRReg, 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, ContaminatedMixt, CopulaCenR, crtests, CSUV, CTShiny, CTShiny2, cytominer, DamiaNN, DaMiRseq, datafsm, dissever, DMTL, driveR, dtwSat, eclust, Ecume, ensembleR, fairness, fdm2id, featuretoolsR, fieldRS, fmf, foster, FSinR, FuncNN, glmdisc, glmtree, GPCMlasso, healthcareai, JFE, KCSKNNShiny, KCSNBShiny, KNNShiny, KnowSeq, LassoGEE, latrend, lilikoi, LncFinder, LPRelevance, m2b, MAIT, mand, mcca, metabCombiner, MetabolomicsBasics, MetaClean, metaEnsembleR, MiDA, mikropml, MLDAShiny, MLDAShiny2, mlquantify, MNLR, modelgrid, mosaicModel, MRFcov, MSstatsSampleSize, multiclassPairs, NBShiny, NBShiny2, NBShiny3, nbTransmission, NeuralSens, nnGarrote, NNS, NoiseFiltersR, nonet, NonProbEst, oncrawlR, panelWranglR, ParallelDSM, parboost, Pi, POMA, preciseTAD, PredPsych, predtoolsTS, PriceIndices, pRoloc, quantable, RadialVisGadgets, RaSEn, RelimpPCR, REMP, RISCA, rmda, RMKL, rModeling, RStoolbox, scGPS, sentometrics, shinyr, SLEMI, smartR, soilassessment, Sojourn, Sojourn.Data, specmine, splitSelect, ssr, stepPenal, studyStrap, SubCellBarCode, swag, TBSignatureProfiler, TCGAbiolinksGUI, TestDimorph, TLBC, TrafficBDE, transcriptR, varEst, waterquality, waves, WRTDStidal |
| Reverse suggests: |
AppliedPredictiveModeling, aurelius, aVirtualTwins, breakDown, broom, butcher, CBDA, cellity, ciu, condvis2, Cubist, deepboost, discSurv, DNAshapeR, doParallel, doSNOW, easyalluvial, ENMTools, EventDetectR, FCBF, flashlight, GAparsimony, genefu, GSIF, idm, iml, imputeR, iprior, lulcc, metaforest, metamicrobiomeR, MLInterfaces, mlr, mlr3filters, mmb, modelplotr, moreparty, NeuralNetTools, opera, ordinalClust, pdp, pmml, r2pmml, randomForestSRC, regsem, RGCxGC, rScudo, SAMtool, shapr, SLOPE, SmartMeterAnalytics, spectacles, spFSR, ssc, SSLR, strip, SuperLearner, superml, varrank, vip, xspliner |
| Reverse enhances: |
bestglm, prediction |