E2E: An R Package for Easy‐to‐Build Ensemble Models
Year: 2025
Type: article
Abstract: ABSTRACT E2E (Easy to Ensemble) is an R package aiming to provide researchers with a simple, user‐friendly, and comprehensive ensemble learning framework to address the challenges of existing tools when dealing with imbalanced data or constructing complex models. E2E supports various ensemble strategies, such as bagging, stacking, and voting, and two major application scenarios: diagnosis (binary classification) and prognosis (survival analysis), with built‐in base models for both diagnosis and prognosis. The authors demonstrated that E2E performs excellently in handling imbalanced classification and survival prediction tasks on the TCGA and CHARLS datasets. Updates and detailed usage tutorials can be found on GitHub, CRAN, and WeChat official account.
Source: Med Research
DOI: 10.1002/mdr2.70030
Authors: Shanjie Luan, Ximing Wang
Institutions: Shandong University, South China University of Technology
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4414358207