Fairlearn swMATH ID: 36560 Software Authors: Bird, S.; ık, M. Dud; Edgar, R.; Horn, B.; Lutz, R.; Milan, V.; Sameki, M.; Wallach, H.; Walker, K. Description: 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 a Jupyter widget for model assessment. Besides the source code, this repository also contains Jupyter notebooks with examples of Fairlearn usage. Homepage: https://fairlearn.github.io Source Code: https://github.com/fairlearn/fairlearn Dependencies: Python Related Software: AIF360; H2O; DALEX; Alibi; shap; XGBoost; NumPy; Scikit; LightGBM; modelStudio; TensorFlow; Aequitas; PDPbox; AI Explainability 360; dalex; UCI-ml; Alibi Explain; GitHub; plotly.py; iNNvestigate Cited in: 3 Documents all top 5 Cited by 12 Authors 1 Baniecki, Hubert 1 Biecek, Przemysław 1 Henzinger, Thomas A. 1 Karimi, Mahyar 1 Kretowicz, Wojciech 1 Kueffner, Konstantin 1 Mallik, Kaushik 1 Panero, Francesca 1 Piątyszek, Piotr 1 Proissl, Manuel 1 Scutari, Marco 1 Wiśniewski, Jakub Cited in 2 Serials 1 Journal of Machine Learning Research (JMLR) 1 Statistics and Computing Cited in 2 Fields 3 Computer science (68-XX) 1 Statistics (62-XX) Citations by Year