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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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Install

install.packages('SuperLearner')

Monthly Downloads

9,035

Version

2.0-41

License

GPL-3

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Maintainer

Eric Polley

Last Published

August 21st, 2026

Functions in SuperLearner (2.0-41)

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