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Rashomon Capacity: A Metric for Predictive Multiplicity in Classification. (arXiv:2206.01295v2 [cs.LG] UPDATED)
Oct. 21, 2022, 1:14 a.m. | Hsiang Hsu, Flavio du Pin Calmon
stat.ML updates on arXiv.org arxiv.org
Predictive multiplicity occurs when classification models with statistically
indistinguishable performances assign conflicting predictions to individual
samples. When used for decision-making in applications of consequence (e.g.,
lending, education, criminal justice), models developed without regard for
predictive multiplicity may result in unjustified and arbitrary decisions for
specific individuals. We introduce a new metric, called Rashomon Capacity, to
measure predictive multiplicity in probabilistic classification. Prior metrics
for predictive multiplicity focus on classifiers that output thresholded (i.e.,
0-1) predicted classes. In contrast, Rashomon Capacity …
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