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Erschienen in:
2013 | OriginalPaper | Buchkapitel
Area under the Precision-Recall Curve: Point Estimates and Confidence Intervals
verfasst von : Kendrick Boyd, Kevin H. Eng, C. David Page
Erschienen in: Machine Learning and Knowledge Discovery in Databases
Verlag: Springer Berlin Heidelberg
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The area under the precision-recall curve (AUCPR) is a single number summary of the information in the precision-recall (PR) curve. Similar to the receiver operating characteristic curve, the PR curve has its own unique properties that make estimating its enclosed area challenging. Besides a point estimate of the area, an interval estimate is often required to express magnitude and uncertainty. In this paper we perform a computational analysis of common AUCPR estimators and their confidence intervals. We find both satisfactory estimates and invalid procedures and we recommend two simple intervals that are robust to a variety of assumptions.