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Implements the super learner prediction method and contains a library of prediction algorithms to be used in the super learner.
| Version: | 2.0-29 |
| Depends: | R (≥ 2.14.0), nnls, gam (≥ 1.15) |
| Imports: | cvAUC, methods |
| 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 (≥ 0.6) |
| Published: | 2024-02-20 |
| DOI: | 10.32614/CRAN.package.SuperLearner |
| Author: | Eric Polley [aut, cre], Erin LeDell [aut], Chris Kennedy [aut], Sam Lendle [ctb], Mark van der Laan [aut, ths] |
| Maintainer: | Eric Polley <epolley at uchicago.edu> |
| License: | GPL-3 |
| URL: | https://github.com/ecpolley/SuperLearner |
| NeedsCompilation: | no |
| Materials: | NEWS ChangeLog |
| In views: | Bayesian, MachineLearning |
| CRAN checks: | SuperLearner results |
| Reference manual: | SuperLearner.pdf |
| Vignettes: |
Guide to SuperLearner |
| Package source: | SuperLearner_2.0-29.tar.gz |
| Windows binaries: | r-devel: SuperLearner_2.0-29.zip, r-release: SuperLearner_2.0-29.zip, r-oldrel: SuperLearner_2.0-29.zip |
| macOS binaries: | r-release (arm64): SuperLearner_2.0-29.tgz, r-oldrel (arm64): SuperLearner_2.0-29.tgz, r-release (x86_64): SuperLearner_2.0-29.tgz, r-oldrel (x86_64): SuperLearner_2.0-29.tgz |
| Old sources: | SuperLearner archive |
| Reverse depends: | ctmle, EScvtmle, polle, subsemble, survML, tmle |
| Reverse imports: | AIPW, amp, CausalGPS, CausalMetaR, causalweight, CIMTx, CompMix, CRE, crossurr, DeepLearningCausal, DRDRtest, drpop, drtmle, evalITR, flevr, GPCERF, lmtp, nlpred, PSweight, Ricrt, RISCA, RobinCar, superMICE, tehtuner, tidyhte, vaccine, vimp |
| Reverse suggests: | biotmle, gKRLS, hal9001, ltmle, medflex, nestedcv, riskRegression, targeted, vglmer, WeightIt |
Please use the canonical form https://CRAN.R-project.org/package=SuperLearner to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.