[2605.00926] A Review of the Receiver Operating Characteristic Curve and a Proof About the Area Beneath It
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Computer Science > Machine Learning
arXiv:2605.00926 (cs)
[Submitted on 30 Apr 2026]
Title:A Review of the Receiver Operating Characteristic Curve and a Proof About the Area Beneath It
Authors:Steven Redolfi
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Abstract:The Receiver Operating Characteristic (ROC) curve of a binary classifier has often been utilized to measure the performance of the classifier. The area beneath this curve is used in particular because of its quoted probabilistic interpretation as being equal to the probability that the classifier will rank a random positive observation above a random negative observation. This paper formalizes this claim, produces a bound on how far away from the truth it is if a hypothesis is not met, and gives a small literature review of the ROC curve.
Subjects:
Machine Learning (cs.LG); Probability (math.PR)
Cite as: arXiv:2605.00926 [cs.LG]
(or arXiv:2605.00926v1 [cs.LG] for this version)
https://doi.org/10.48550/arXiv.2605.00926
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arXiv-issued DOI via DataCite
Submission history
From: Steven Redolfi [view email] [v1] Thu, 30 Apr 2026 18:55:43 UTC (8 KB)
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