Trusted-AI/AIF360
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.
Provides pre- and in-processing debiasing algorithms (reweighting, disparate impact removal, adversarial debiasing) alongside 20+ fairness metrics spanning group fairness, individual fairness, and sample distortion measures. Available in both Python and R with modular dependencies, allowing users to install only required algorithm backends (TensorFlow for adversarial debiasing, CVXPY for optimization-based methods). Extensible architecture designed for research-to-practice translation across finance, HR, healthcare, and education domains.
2,763 stars and 34,451 monthly downloads. Used by 3 other packages. Available on PyPI.
Stars
2,763
Forks
902
Language
Python
License
Apache-2.0
Category
Last pushed
Nov 13, 2025
Monthly downloads
34,451
Commits (30d)
0
Dependencies
5
Reverse dependents
3
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