223  fairlearn(1) - Kailash Tool Reference

223.1 fairlearn

fairlearn - Fairlearn — fairness metrics and mitigation algorithms for ML models.

Layer DEFENCE
Category d-03-assurance-evals-benchmarks
Safety class safe
Licence MIT
Upstream github.com/fairlearn/fairlearn

223.1.1 NAME

fairlearn - Fairlearn — fairness metrics and mitigation algorithms for ML models.

223.1.2 SYNOPSIS

Not derived automatically - see upstream documentation. This page does not hand-copy flags (generation contract, ADR-0001).

223.1.3 DESCRIPTION (upstream)

Fairlearn ========= Fairlearn is a Python package that empowers developers of artificial intelligence (AI) systems to assess their system’s fairness and mitigate any observed unfairness issues. Fairlearn contains mitigation algorithms as well as metrics for model assessment. Besides the source code, this repository also contains Jupyter notebooks with examples of Fairlearn usage. Website: https://fairlearn.org/ - What we mean by *fairness* <#what-we-mean-by-fairness>__ - Overview of Fairlearn <#overview-of-fairlearn>__ - Getting started with fairlearn <#getting-started-with-fairlearn>__ - Maintainers <#maintainers>__ - Code of conduct <#code-of-conduct>__ - Issues <#issues>

223.1.4 SEE ALSO

ref: pin - verified 2026-10-14