SuperLearner: Super Learner Prediction

Implements the super learner prediction method and contains a library of prediction algorithms to be used in the super learner.

Version: 2.0-26
Depends: R (≥ 2.14.0), nnls
Imports: cvAUC
Suggests: arm, bartMachine, biglasso, bigmemory, caret, class, devtools, e1071, earth, extraTrees, gam (≥ 1.15), 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: 2019-12-10
Author: Eric Polley [aut, cre], Erin LeDell [aut], Chris Kennedy [aut], Sam Lendle [ctb], Mark van der Laan [aut, ths]
Maintainer: Eric Polley <polley.eric at>
License: GPL-3
NeedsCompilation: no
Materials: NEWS ChangeLog
In views: MachineLearning
CRAN checks: SuperLearner results


Reference manual: SuperLearner.pdf
Vignettes: Guide to SuperLearner
Package source: SuperLearner_2.0-26.tar.gz
Windows binaries: r-devel:, r-devel-gcc8:, r-release:, r-oldrel:
OS X binaries: r-release: SuperLearner_2.0-26.tgz, r-oldrel: SuperLearner_2.0-26.tgz
Old sources: SuperLearner archive

Reverse dependencies:

Reverse depends: ctmle, tmle
Reverse imports: CBDA, ck37r, drtmle, expose, nlpred, survtmle, vimp
Reverse suggests: ltmle, medflex, riskRegression, tmle.npvi, WeightIt


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