Getfair: Generalized fairness tuning of classification models


Sikdar, Sandipan ; Lemmerich, Florian ; Strohmaier, Markus



DOI: https://doi.org/10.1145/3531146.3533094
URL: https://dl.acm.org/doi/10.1145/3531146.3533094
Document Type: Conference or workshop publication
Year of publication: 2022
Book title: Proceedings of 2022 5th ACM Conference on Fairness, Accountability, and Transparency (FAccT 2022) : June 21-24, 2022, Seoul, Korea
Page range: 289-299
Conference title: FAccT '22, 5. Annual ACM FAccT Conference 2022
Location of the conference venue: Seoul, South Korea
Date of the conference: 21.-24.06.2022
Publisher: Isbell, Charles ; Lazar, Seth ; Oh, Alice ; Xiang, Alice
Place of publication: New York, NY
Publishing house: ACM
ISBN: 978-1-4503-9352-2
Publication language: English
Institution: Business School > Data Science in the Economic and Social Sciences (Strohmaier, 2022-)
Subject: 000 Generalities
Keywords (English): fair classification , fairness metrics , sensitive attribute , classifier models




Dieser Eintrag ist Teil der Universitätsbibliographie.




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