| create.Learner | Factory for learner wrappers |
| create.SL.xgboost | Factory for XGBoost SL wrappers |
| CVFolds | Generate list of row numbers for each fold in the... |
| CV.SuperLearner | Function to get V-fold cross-validated risk estimate for... |
| listWrappers | list all wrapper functions in SuperLearner |
| plot.CV.SuperLearner | Graphical display of the V-fold CV risk estimates |
| predict.SL.bartMachine | bartMachine prediction |
| predict.SL.biglasso | Prediction wrapper for SL.biglasso |
| predict.SL.glm | Prediction for SL.glm |
| predict.SL.glmnet | Prediction for an SL.glmnet object |
| predict.SL.kernelKnn | Prediction for SL.kernelKnn |
| predict.SL.ksvm | Prediction for SL.ksvm |
| predict.SL.lda | Prediction wrapper for SL.lda |
| predict.SL.lm | Prediction for SL.lm |
| predict.SL.qda | Prediction wrapper for SL.qda |
| predict.SL.ranger | Prediction wrapper for ranger random forests |
| predict.SL.speedglm | Prediction for SL.speedglm |
| predict.SL.speedlm | Prediction for SL.speedlm |
| predict.SL.xgboost | XGBoost prediction on new data |
| predict.superlearner | Predict method for SuperLearner object |
| recombineCVSL | Recombine a CV.SuperLearner fit using a new metalearning... |
| recombineSL | Recombine a SuperLearner fit using a new metalearning method |
| SampleSplitSuperLearner | Super Learner Prediction Function |
| SL.bartMachine | Wrapper for bartMachine learner |
| SL.biglasso | SL wrapper for biglasso |
| SL.cforest | cforest (party) |
| SL.glm | Wrapper for glm |
| SL.glmnet | Elastic net regression, including lasso and ridge |
| SL.kernelKnn | SL wrapper for KernelKNN |
| SL.ksvm | Wrapper for Kernlab's SVM algorithm |
| SL.lda | SL wrapper for MASS:lda |
| SL.lm | Wrapper for lm |
| SL.qda | SL wrapper for MASS:qda |
| SL.ranger | SL wrapper for ranger |
| SL.speedglm | Wrapper for speedglm |
| SL.speedlm | Wrapper for speedlm |
| SL.xgboost | XGBoost SuperLearner wrapper |
| summary.CV.SuperLearner | Summary Function for Cross-Validated Super Learner |
| SuperLearner | Super Learner Prediction Function |
| SuperLearner.control | Control parameters for the SuperLearner |
| SuperLearner.CV.control | Control parameters for the cross validation steps in... |
| SuperLearnerNews | Show the NEWS file for the SuperLearner package |
| trimLogit | truncated-probabilities logit transformation |
| write.method.template | Method to estimate the coefficients for the super learner |
| write.screen.template | screening algorithms for SuperLearner |
| write.SL.template | Wrapper functions for prediction algorithms in SuperLearner |
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