Fairbeat: Assessing and Mitigating Bias with the Composite Balance Score
Published in ECML-PKKD (Demo Track), 2025
Publication following my Master’s thesis internship at Fujistsu Luxembourg, under the supervision of Sofiane Lagraa and Moussa Ouedraogo.
We developped a simple composite metric based on the balance of protected attributes (gender, age, ethnicity, etc.) in tabular dataset, the Composite Balance Score (CBS), which correlates with bias in models after training on the data. We developped a web interface to evaluate any tabular dataset, re-balance it using different mitigation strategies, and train machine learning models and the balanced data.
Recommended citation: Lequeu, P. A., Lagraa, S., Robin, G., & Ouedraogo, M. (2025, September). Fairbeat: Assessing and Mitigating Bias with the Composite Balance Score. In Joint European Conference on Machine Learning and Knowledge Discovery in Databases (pp. 475-480). Cham: Springer Nature Switzerland.
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