E2E is a comprehensive R package designed tostreamline the development, evaluation, and interpretation of machinelearning models for bothdiagnostic (classification)andprognostic (survival analysis) tasks. It provides arobust, extensible framework for training individual models and buildingpowerful ensembles—including Bagging, Voting, and Stacking—with minimalcode. The package also includes integrated tools for visualization andmodel explanation via SHAP values.
Author: Shanjie Luan (ORCID: 0009-0002-8569-8526,First and Corresponding Author), Ximing Wang
Citation: If you use E2E in your research, pleasecite it as: “Luan, S. and Wang, X. (2025), E2E: An R Package forEasy-to-Build Ensemble Models. Med Research.https://doi.org/10.1002/mdr2.70030”
Note: The article is open source on CRAN and Githuband is free to use, but you have to cite our article if you use E2E inyour research. If you have any questions, please contactLuan20050519@163.com.
For complete documentation, tutorials, and functionreferences, please visit our pkgdown website:
https://XIAOJIE0519.github.io/E2E/
back to our github website:
https://github.com/XIAOJIE0519/E2E
The development version of E2E can be installed directly from GitHubusingremotes.
# If you don't have remotes, install it first:# install.packages("remotes")remotes::install_github("XIAOJIE0519/E2E")After installation, load the package into your R session:
library(E2E)