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Oct, 2019
多敏感属性聚类的公平性
Fairness in Clustering with Multiple Sensitive Attributes
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Savitha Sam Abraham, Deepak P, Sowmya S Sundaram
TL;DR
本文提出了一种公平的聚类方法FairKM，它基于流行的K-Means聚类公式，通过计算公平性与集群一致性目标，得到了公平的聚类。实证评估表明，FairKM产生的集群在聚类质量和对敏感属性组的公平呈现方面都有显著提高。
Abstract
A clustering may be considered as fair on pre-specified
sensitive attributes
if the proportions of sensitive attribute groups in each cluster reflect that in the dataset. In this paper, we consider the task of
fair clus
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