Package: SuperLearner 2.0-30-9000

Eric Polley

SuperLearner: Super Learner Prediction

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

Authors:Eric Polley [aut, cre], Erin LeDell [aut], Chris Kennedy [aut], Sam Lendle [ctb], Mark van der Laan [aut, ths]

SuperLearner_2.0-30-9000.tar.gz
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SuperLearner.pdf |SuperLearner.html✨
SuperLearner/json (API)
NEWS

# Install 'SuperLearner' in R:
install.packages('SuperLearner', repos = c('https://ledell.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/ecpolley/superlearner/issues

On CRAN:

13.23 score 272 stars 36 packages 1.8k scripts 3.6k downloads 56 mentions 117 exports 9 dependencies

Last updated 9 months agofrom:8b521abf05. Checks:OK: 3 NOTE: 4. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 01 2024
R-4.5-winNOTENov 01 2024
R-4.5-linuxNOTENov 01 2024
R-4.4-winNOTENov 01 2024
R-4.4-macNOTENov 01 2024
R-4.3-winOKNov 01 2024
R-4.3-macOKNov 01 2024

Exports:Allcoef.CV.SuperLearnercoef.SuperLearnercreate.Learnercreate.SL.xgboostCV.SuperLearnerCVFoldslistWrappersmcSuperLearnermethod.AUCmethod.CC_LSmethod.CC_nloglikmethod.NNloglikmethod.NNLSmethod.NNLS2method.templateplot.CV.SuperLearnerpredict.SL.bartMachinepredict.SL.bayesglmpredict.SL.biglassopredict.SL.caretpredict.SL.cforestpredict.SL.earthpredict.SL.gampredict.SL.gbmpredict.SL.glmpredict.SL.glmnetpredict.SL.ipredbaggpredict.SL.kernelKnnpredict.SL.knnpredict.SL.ksvmpredict.SL.ldapredict.SL.leekassopredict.SL.lmpredict.SL.loesspredict.SL.logregpredict.SL.meanpredict.SL.nnetpredict.SL.nnlspredict.SL.polymarspredict.SL.qdapredict.SL.randomForestpredict.SL.rangerpredict.SL.ridgepredict.SL.rpartpredict.SL.speedglmpredict.SL.speedlmpredict.SL.steppredict.SL.stepAICpredict.SL.svmpredict.SL.templatepredict.SL.xgboostpredict.SuperLearnerprint.CV.SuperLearnerprint.summary.CV.SuperLearnerprint.SuperLearnerrecombineCVSLrecombineSLSampleSplitSuperLearnerscreen.corPscreen.corRankscreen.glmnetscreen.randomForestscreen.SISscreen.templatescreen.ttestSL.bartMachineSL.bayesglmSL.biglassoSL.caretSL.caret.rpartSL.cforestSL.earthSL.gamSL.gbmSL.glmSL.glm.interactionSL.glmnetSL.ipredbaggSL.kernelKnnSL.knnSL.ksvmSL.ldaSL.leekassoSL.lmSL.loessSL.logregSL.meanSL.nnetSL.nnlsSL.polymarsSL.qdaSL.randomForestSL.rangerSL.ridgeSL.rpartSL.rpartPruneSL.speedglmSL.speedlmSL.stepSL.step.forwardSL.step.interactionSL.stepAICSL.svmSL.templateSL.xgboostsnowSuperLearnersummary.CV.SuperLearnerSuperLearnerSuperLearner.controlSuperLearner.CV.controlSuperLearnerDocsSuperLearnerNewstrimLogitwrite.method.templatewrite.screen.templatewrite.SL.template

Dependencies:bitopscaToolscvAUCdata.tablegplotsgtoolsKernSmoothnnlsROCR

Guide to SuperLearner

Chris Kennedy, University of California, Berkeley

Rendered fromGuide-to-SuperLearner.Rmdusingknitr::rmarkdownon Nov 01 2024.

Last update: 2021-03-28
Started: 2017-03-21

Readme and manuals

Help Manual

Help pageTopics
Factory for learner wrapperscreate.Learner
Factory for XGBoost SL wrapperscreate.SL.xgboost
Function to get V-fold cross-validated risk estimate for super learnercoef.CV.SuperLearner CV.SuperLearner print.CV.SuperLearner
Generate list of row numbers for each fold in the cross-validationCVFolds
list all wrapper functions in SuperLearnerlistWrappers
Graphical display of the V-fold CV risk estimatesplot.CV.SuperLearner
bartMachine predictionpredict.SL.bartMachine
Prediction wrapper for SL.biglassopredict.SL.biglasso
Prediction for SL.glmpredict.SL.glm
Prediction for an SL.glmnet objectpredict.SL.glmnet
Prediction for SL.kernelKnnpredict.SL.kernelKnn
Prediction for SL.ksvmpredict.SL.ksvm
Prediction wrapper for SL.ldapredict.SL.lda
Prediction for SL.lmpredict.SL.lm
Prediction wrapper for SL.qdapredict.SL.qda
Prediction wrapper for ranger random forestspredict.SL.ranger
Prediction for SL.speedglmpredict.SL.speedglm
Prediction for SL.speedlmpredict.SL.speedlm
XGBoost prediction on new datapredict.SL.xgboost
Predict method for SuperLearner objectpredict.SuperLearner
Recombine a CV.SuperLearner fit using a new metalearning methodrecombineCVSL
Recombine a SuperLearner fit using a new metalearning methodrecombineSL
Super Learner Prediction FunctionSampleSplitSuperLearner
Wrapper for bartMachine learnerSL.bartMachine
SL wrapper for biglassoSL.biglasso
cforest partySL.cforest
Wrapper for glmSL.glm
Elastic net regression, including lasso and ridgeSL.glmnet
SL wrapper for KernelKNNSL.kernelKnn
Wrapper for Kernlab's SVM algorithmSL.ksvm
SL wrapper for MASS:ldaSL.lda
Wrapper for lmSL.lm
SL wrapper for MASS:qdaSL.qda
SL wrapper for rangerSL.ranger
Wrapper for speedglmSL.speedglm
Wrapper for speedlmSL.speedlm
XGBoost SuperLearner wrapperSL.xgboost
Summary Function for Cross-Validated Super Learnerprint.summary.CV.SuperLearner summary.CV.SuperLearner
Super Learner Prediction Functioncoef.SuperLearner mcSuperLearner print.SuperLearner snowSuperLearner SuperLearner
Control parameters for the SuperLearnerSuperLearner.control
Control parameters for the cross validation steps in 'SuperLearner'SuperLearner.CV.control
Show the NEWS file for the SuperLearner packageSuperLearnerDocs SuperLearnerNews
truncated-probabilities logit transformationtrimLogit
Method to estimate the coefficients for the super learnermethod.AUC method.CC_LS method.CC_nloglik method.NNloglik method.NNLS method.NNLS2 method.template write.method.template
screening algorithms for SuperLearnerAll screen.corP screen.corRank screen.glmnet screen.randomForest screen.SIS screen.template screen.ttest write.screen.template
Wrapper functions for prediction algorithms in SuperLearnerpredict.SL.bayesglm predict.SL.caret predict.SL.cforest predict.SL.earth predict.SL.gam predict.SL.gbm predict.SL.ipredbagg predict.SL.knn predict.SL.leekasso predict.SL.loess predict.SL.logreg predict.SL.mean predict.SL.nnet predict.SL.nnls predict.SL.polymars predict.SL.randomForest predict.SL.ridge predict.SL.rpart predict.SL.step predict.SL.stepAIC predict.SL.svm predict.SL.template SL.bayesglm SL.caret SL.caret.rpart SL.earth SL.gam SL.gbm SL.glm.interaction SL.ipredbagg SL.knn SL.leekasso SL.loess SL.logreg SL.mean SL.nnet SL.nnls SL.polymars SL.randomForest SL.ridge SL.rpart SL.rpartPrune SL.step SL.step.forward SL.step.interaction SL.stepAIC SL.svm SL.template write.SL.template