Implements the super learner prediction method and contains a library of prediction algorithms to be used in the super learner.
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2.0-42 by Eric Polley, a month ago
https://github.com/ecpolley/SuperLearner
Browse source code at https://github.com/cran/SuperLearner
Authors: Eric Polley [aut, cre] , Erin LeDell [aut] , Chris Kennedy [aut] , Sam Lendle [ctb] , Mark van der Laan [aut, ths]
Documentation: PDF Manual
GPL-3 license
Imports cvAUC, methods, rlang
Depends on gam, nnls
Suggests arm, bartMachine, biglasso, bigmemory, caret, class, devtools, e1071, earth, gbm, genefilter, ggplot2, glmnet, ipred, KernelKnn, kernlab, knitr, lattice, LogicReg, MASS, mlbench, nloptr, nnet, party, polspline, prettydoc, quadprog, randomForest, ranger, RhpcBLASctl, ROCR, rmarkdown, rpart, SIS, speedglm, spls, sva, testthat, xgboost
Imported by AIPW, CICI, CIMTx, CRE, CausalGPS, CausalMetaR, CausalState, CompMix, DeepLearningCausal, PLUCR, PND.heter.cluster, PSor, PSweight, RISCA, Ricrt, RobinCar, amp, crossurr, drpop, drtmle, evalITR, flevr, flexCausal, lmtp, tehtuner, tidyhte, vaccine, vimp.
Depended on by bartXViz, ctmle, subsemble, survML, tmle, tradeoffaucdim.
Suggested by CanonicalFamilyExtra, MRTAnalysis, WeightIt, causaldef, futurize, gKRLS, hal9001, ltmle, lvimp, medflex, nestedcv, polle, psAve, riskRegression, targeted, vglmer.
See at CRAN