A Suite of Fairness Datasets for Tabular Classification

• URL: http://arxiv.org/abs/2308.00133v1
• Date: Mon, 31 Jul 2023 19:58:12 GMT
• Title: A Suite of Fairness Datasets for Tabular Classification
• Authors: Martin Hirzel, Michael Feffer
• Abstract summary: We introduce a suite of functions for fetching 20 fairness datasets and providing associated fairness metadata. Hopefully, these will lead to more rigorous experimental evaluations in future fairness-aware machine learning research.
• Score: 2.0813318162800707
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: There have been many papers with algorithms for improving fairness of machine-learning classifiers for tabular data. Unfortunately, most use only very few datasets for their experimental evaluation. We introduce a suite of functions for fetching 20 fairness datasets and providing associated fairness metadata. Hopefully, these will lead to more rigorous experimental evaluations in future fairness-aware machine learning research.

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