Improved Balanced Random Forest (iBRF): A flexible hybrid resampling-bagging framework for crash severity classification in imbalanced datasets
The iBRF algorithm not only enhances classification performance but also helps identify risk factors associated with the minority class, which almost always correspond to severe‑outcome crashes and the focus of studies.
Authors
- Seyed Iman Mohammadpour (ORCID: https://orcid.org/0000-0002-6878-6818)
- Javadreza Vahedi (ORCID: https://orcid.org/0000-0002-4244-3833)
Institutions
- University of Bojnord (IR)
Publication Details
- Journal
- Traffic Injury Prevention
- Published
- 2026-02-18
- DOI
- https://doi.org/10.1080/15389588.2025.2610428
- Primary Topic
- Imbalanced Data Classification Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00