16 skills found
ecpolley / SuperLearnerCurrent version of the SuperLearner R package
dlab-berkeley / Machine Learning In RWorkshop (6 hours): preprocessing, cross-validation, lasso, decision trees, random forest, xgboost, superlearner ensembles
ck37 / Superlearner GuideSuperLearner guide: fitting models, ensembling, prediction, hyperparameters, parallelization, timing, feature selection, etc.
kathoffman / Lmtp TutorialCorresponding code guide to the tutorial paper "Introducing longitudinal modified treatment policies: a unified framework for studying complex exposures" (Hoffman et al., 2023)
lendle / SuPyLearnerAn implementation of the SuperLearner algorithm in Python based on scikit-learn.
ecpolley / SuperLearnerExtraAdditional functions for the SuperLearner R package. A collection of mostly wrapper functions that might be useful for the SuperLearner but are not general enough to be placed in the main package.
ck37 / Ck37rR functions for project setup, data cleaning, machine learning, SuperLearner, parallelization, and targeted learning.
ck37 / Predictive Modeling In RWorkshop (2-6 hours): cleaning, missing value imputation, EDA, ensemble learning, calibration, variable importance ranking, accumulated local effect plots. WIP.
ainaimi / SuperLearnerIntroNo description available
nt-williams / Mlr3superlearnerSuper learner fitting and prediction using mlr3
osofr / GridislDiscrete SuperLearner with Grid-Search for Longitudinal Data
ck37 / FeaturerankEnsemble feature ranking for SuperLearner variable selection
ecpolley / NCI60 SuperLearnerCode and data for running the super learner with the NCI60 human tumor cell lines
nshkrdotcom / SuperlearnerOTP Supervisor Educational Platform
BerkeleyBiostats / SuperLearner SASSuperLearner SAS macro
ruthkeogh / Superlearner Survival TutorialThe super learner for time-to-event outcomes: A tutorial. Ruth Keogh, Karla Diaz-Ordaz, Nan van Geloven, Jon Michael Gran, Kamaryn Tanner. https://arxiv.org/abs/2509.03315
