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Fairness for AUC via Feature Augmentation. (arXiv:2111.12823v2 [cs.LG] UPDATED)
Aug. 25, 2022, 1:12 a.m. | Hortense Fong, Vineet Kumar, Anay Mehrotra, Nisheeth K. Vishnoi
stat.ML updates on arXiv.org arxiv.org
We study fairness in the context of classification where the performance is
measured by the area under the curve (AUC) of the receiver operating
characteristic. AUC is commonly used to measure the performance of prediction
models. The same classifier can have significantly varying AUCs for different
protected groups and, in real-world applications, it is often desirable to
reduce such cross-group differences. We address the problem of how to acquire
additional features to most greatly improve AUC for the disadvantaged group. …
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