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BORG: Bounded Outcome Risk Guard for Model Evaluation
Automatically detects and enforces valid model evaluation by identifying information reuse between training and evaluation data. Guards against data leakage, look-ahead bias, and invalid cross-validation schemes that inflate performance estimates. Supports temporal, spatial, and grouped evaluation structures. Based on evaluation principles described in Roberts et al. (2017) <doi:10.1111/ecog.02881>, Kaufman et al. (2012) <doi:10.1145/2382577.2382579>, and Kapoor & Narayanan (2023) <doi:10.1016/j.patter.2023.100804>.
Getting started
Browse package contents
Package details |
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| Author | Gilles Colling [aut, cre, cph] (ORCID: <https://orcid.org/0000-0003-3070-6066>) |
| Maintainer | Gilles Colling <gilles.colling051@gmail.com> |
| License | MIT + file LICENSE |
| Version | 0.2.5 |
| URL | https://github.com/gcol33/BORG https://gillescolling.com/BORG/ |
| Package repository | View on CRAN |
| Installation |
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