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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