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Identifying Representational Biases in Datasets Using PCA: A Max-Disparity Partition Framework
Principal Component Analysis (PCA) minimises aggregate reconstruction error, which can inadvertently represent majority subgroups with substantially higher fidelity than minority subgroups. Fairness-aware extensions of PCA correct this disparity but require group labels as input. We address the logi
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