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Oxford University Press (OUP), Bioinformatics, 10(26), p. 1348-1356

DOI: 10.1093/bioinformatics/btq140

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A CROC stronger than ROC: measuring, visualizing and optimizing early retrieval

Journal article published in 2010 by S. Joshua Swamidass, Chloé-Agathe Azencott, Kenny Daily ORCID, Pierre Baldi
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Motivation: The performance of classifiers is often assessed using Receiver Operating Characteristic ROC [or (AC) accumulation curve or enrichment curve] curves and the corresponding areas under the curves (AUCs). However, in many fundamental problems ranging from information retrieval to drug discovery, only the very top of the ranked list of predictions is of any interest and ROCs and AUCs are not very useful. New metrics, visualizations and optimization tools are needed to address this ‘early retrieval’ problem.