A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
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Updated
Jun 15, 2026 - Python
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
Python code for training fair logistic regression classifiers.
⚖️ Fair ML in credit scoring: Assessment, implementation and profit implications
A cryptohauntology correspondence study framework
Emotional Mnemonic Discrimination Task (A and B matched versions)
Statistical analysis of features able to discriminate between low and high grade brain tumor H&E images
Some @scikit-learn compatible tools to address fairness issues in classification problems.
Proxy discrimination auditing for UK insurance pricing models. FCA Consumer Duty compliance, Equality Act 2010, exposure-weighted fairness metrics.
Proxy discrimination auditing for insurance pricing — FCA EP25/2, Consumer Duty, bias metrics
Optimal transport discrimination-free pricing - Lindholm marginalisation, causal path decomposition, Wasserstein barycenter, FCA EP25/2 compliance (145 tests)
Outil d'analyse, de projection et de prévention des discriminations à l'embauche. Développé dans une approche Data Engineering, ce projet agrège des données juridiques historiques, des tendances sociétales et des modèles prédictifs pour fournir une évaluation des risques sectoriels.
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