Published July 13, 2026
| Version v1.1.4
Software
Open
Fairness Auditing in Tabular Machine Learning: A Multi-Dataset Benchmark of Bias, Mitigation, and Robustness
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Description
Final Q1 submission reproducibility package for the manuscript Fairness Auditing in Tabular Machine Learning: A Multi-Dataset Benchmark of Bias, Mitigation, and Robustness. This release includes processed outputs, analysis code, SAM-Fair selection scripts, robustness checks, XGBoost-EG probe outputs, subgroup sensitivity outputs, optional sensitivity analyses, supplementary tables, figures, and reproducibility materials.
Files
NullSpace20/fairness-auditing-public-tabular-benchmarks-v1.1.4.zip
Additional details
Related works
- Is supplement to
- Software: https://github.com/NullSpace20/fairness-auditing-public-tabular-benchmarks/tree/v1.1.4 (URL)