Ensemble Learning Framework for Diagnostic and Prognostic Modeling R package E2E version 0.1.3 Provides a framework to build and evaluate diagnosis or prognosis models using stacking, voting, and bagging ensemble techniques with various base learners. The package also includes tools for visualization and interpretation of models. The development version of the package is available on 'GitHub' at <https://github.com/xiaojie0519/E2E>. The methods are based on the foundational work of Breiman (1996) <doi:10.1007/BF00058655> on bagging and Wolpert (1992) <doi:10.1016/S0893-6080(05)80023-1> on stacking. Software Depends: R (>= 3.5) Imports: caret, dplyr, tidyr, gbm, ggplot2, glmnet, magrittr, MASS, patchwork, pROC, PRROC, randomForestSRC, readr, RSNNS, shapviz, survival, survivalROC, survminer, xgboost, plsRcox, cowplot, Suggests: ada, doParallel, e1071, kernlab, klaR, knitr, nnet, randomForest, RColorBrewer, rmarkdown, rpart, survcomp, Shanjie Luan <Luan20050519@163.com> Comprehensive R Archive Network (CRAN) Shanjie Luan [aut, cre] MIT + file LICENSE (https://CRAN.R-project.org/package=E2E/LICENSE) 2026-03-19 application/tgz https://CRAN.R-project.org/package=E2E doi:10.32614/CRAN.package.E2E en