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A fuzzy-rough uncertainty measure to discover bias encoded explicitly or implicitly in features of structured pattern classification datasets.

, and . Pattern Recognit. Lett., (2022)

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A fuzzy-rough uncertainty measure to discover bias encoded explicitly or implicitly in features of structured pattern classification datasets., and . Pattern Recognit. Lett., (2022)Compatibility of Fairness Metrics with EU Non-Discrimination Laws: Demographic Parity & Conditional Demographic Disparity., , , , , and . CoRR, (2023)Métriques d'équité en Apprentissage Automatique et droit de l'Union Europénne en matière de non-discrimination., , , , , and . CNIA, PFIA, (2023)Measuring Implicit Bias Using SHAP Feature Importance and Fuzzy Cognitive Maps., , , , and . CoRR, (2023)Modeling Implicit Bias with Fuzzy Cognitive Maps., , , , and . CoRR, (2021)A fuzzy-rough uncertainty measure to discover bias encoded explicitly or implicitly in features of structured pattern classification datasets., and . CoRR, (2021)Modeling implicit bias with fuzzy cognitive maps., , , , and . Neurocomputing, (2022)Compatibility of Fairness Metrics With EU Non-Discrimination Law: A Legal and Technical Case Study., , , , , and . EWAF, volume 3442 of CEUR Workshop Proceedings, CEUR-WS.org, (2023)Bias Quantification for Protected Features in Pattern Classification Problems., and . CIARP, volume 12702 of Lecture Notes in Computer Science, page 351-360. Springer, (2021)