Fair Clustering via Equitable Group Representations
Mohsen Abbasi, Aditya Bhaskara, Suresh Venkatasubramanian
Abstract
What does it mean for a clustering to be fair? One popular approach seeks to ensure that each cluster contains groups in (roughly) the same proportion in which they exist in the population. The normative principle at play is balance: any cluster might act as a representative of the data, and thus should reflect its diversity.
Topics & Concepts
Cluster analysisCluster (spacecraft)Group (periodic table)NormativeArtificial intelligenceComputer scienceMathematicsField (mathematics)Data miningCluster groupingRepresentation (politics)Perspective (graphical)Order (exchange)Fuzzy clusteringData-Driven Disease SurveillanceCensus and Population EstimationBayesian Methods and Mixture Models