Can Ensembling Preprocessing Algorithms Lead to Better Machine Learning Fairness?
arxiv(2023)
摘要
In this work, we evaluate three popular fairness preprocessing algorithms and investigate the potential for combining all algorithms into a more robust preprocessing ensemble. We report on lessons learned that can help practitioners better select fairness algorithms for their models.
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关键词
Machine learning algorithms, Computational modeling, Machine learning
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