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How Random is a Classifier given its Area under Curve?

dc.contributor.authorZeinstra,Chris
dc.contributor.authorVeldhuis,Raymond
dc.contributor.authorSpreeuwers,Luuk
dc.contributor.editorBrömme,Arslan
dc.contributor.editorBusch,Christoph
dc.contributor.editorDantcheva,Antitza
dc.contributor.editorRathgeb,Christian
dc.contributor.editorUhl,Andreas
dc.date.accessioned2017-09-26T09:21:01Z
dc.date.available2017-09-26T09:21:01Z
dc.date.issued2017
dc.description.abstractWhen the performance of a classifier is empirically evaluated, the Area Under Curve (AUC) is commonly used as a one dimensional performance measure. In general, the focus is on good performance (AUC towards 1). In this paper, we study the other side of the performance spectrum (AUC towards 0.50) as we are interested to which extend a classifier is random given its AUC. We present the exact probability distribution of the AUC of a truely random classifier, given a finite number of distinct genuine and imposter scores. It quantifies the “randomness” of the measured AUC. The distribution involves the restricted partition function, a well studied function in number theory. Although other work exists that considers confidence bounds on the AUC, the novelty is that we do not assume any underlying parametric or non-parametric model or specify an error rate. Also, in cases in which a limited number of scores is available, for example in forensic case work, the exact distribution can deviate from these models. For completeness, we also present an approximation using a normal distribution and confidence bounds on the AUC.en
dc.identifier.isbn978-3-88579-664-0
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/4657
dc.language.isoen
dc.publisherGesellschaft für Informatik, Bonn
dc.relation.ispartofBIOSIG 2017
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-70
dc.subjectRandom Classifier
dc.subjectAUC
dc.subjectExact Distribution
dc.subjectApproximation
dc.titleHow Random is a Classifier given its Area under Curve?en
gi.citation.endPage266
gi.citation.startPage259
gi.conference.date20.-22. September 2017
gi.conference.locationDarmstadt, Germany
gi.conference.sessiontitleFurther Conference Contributions

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