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SuperLearner (version 2.0-41)
Super Learner Prediction
Description
Implements the super learner prediction method and contains a library of prediction algorithms to be used in the super learner.
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2.0-41
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Install
install.packages('SuperLearner')
Monthly Downloads
9,035
Version
2.0-41
License
GPL-3
Issues
16
Pull Requests
4
Stars
294
Forks
75
Repository
https://github.com/ecpolley/SuperLearner
Maintainer
Eric Polley
Last Published
August 21st, 2026
Functions in SuperLearner (2.0-41)
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SampleSplitSuperLearner
Super Learner Prediction Function
SL.ranger
SL wrapper for ranger
SL.lm
Wrapper for lm
SL.qda
SL wrapper for MASS:qda
SL.speedlm
Wrapper for speedlm
SL.speedglm
Wrapper for speedglm
SL.xgboost
XGBoost SuperLearner wrapper
SuperLearner.CV.control
Control parameters for the cross validation steps in
SuperLearner
SuperLearner.control
Control parameters for the SuperLearner
SuperLearner
Super Learner Prediction Function
predict.SL.biglasso
Prediction wrapper for SL.biglasso
predict.SL.kernelKnn
Prediction for SL.kernelKnn
predict.SL.glmnet
Prediction for an SL.glmnet object
listWrappers
list all wrapper functions in SuperLearner
create.SL.xgboost
Factory for XGBoost SL wrappers
create.Learner
Factory for learner wrappers
plot.CV.SuperLearner
Graphical display of the V-fold CV risk estimates
SuperLearnerNews
Show the NEWS file for the SuperLearner package
predict.SL.glm
Prediction for SL.glm
predict.SL.bartMachine
bartMachine prediction
predict.SL.lm
Prediction for SL.lm
predict.SL.speedlm
Prediction for SL.speedlm
predict.SL.lda
Prediction wrapper for SL.lda
predict.SL.ksvm
Prediction for SL.ksvm
predict.SL.qda
Prediction wrapper for SL.qda
predict.SuperLearner
Predict method for SuperLearner object
predict.SL.xgboost
XGBoost prediction on new data
predict.SL.speedglm
Prediction for SL.speedglm
predict.SL.ranger
Prediction wrapper for ranger random forests
recombineCVSL
Recombine a CV.SuperLearner fit using a new metalearning method
trimLogit
truncated-probabilities logit transformation
write.method.template
Method to estimate the coefficients for the super learner
summary.CV.SuperLearner
Summary Function for Cross-Validated Super Learner
write.screen.template
screening algorithms for SuperLearner
write.SL.template
Wrapper functions for prediction algorithms in SuperLearner
recombineSL
Recombine a SuperLearner fit using a new metalearning method
SL.kernelKnn
SL wrapper for KernelKNN
SL.glm
Wrapper for glm
SL.glmnet
Elastic net regression, including lasso and ridge
CVFolds
Generate list of row numbers for each fold in the cross-validation
SL.cforest
cforest from package party These defaults emulate cforest_unbiased() but allow customization.
SL.bartMachine
Wrapper for bartMachine learner
SL.biglasso
SL wrapper for biglasso
SL.ksvm
Wrapper for Kernlab's SVM algorithm
SL.lda
SL wrapper for MASS:lda
CV.SuperLearner
Function to get V-fold cross-validated risk estimate for super learner