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Estimating a smooth precision-recall curve 1.0

  Date Added: May 20, 2013  |  Visits: 203

Estimating a smooth precision-recall curve

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In binary classification, the precision-recall curve (PRC) has become a widespread conceptual tool for assessing classification performance. The curve relates the positive predictive value of a classifier to its true positive rate and provides a useful alternative to the well-known receiver operating characteristic (ROC). A smooth estimate of the PRC can be computed on the basis of a simple distributional assumption about the underlying decision values.This archive contains an easy-to-use MATLAB implementation of this approach.For full details, see:K.H. Brodersen, C.S. Ong, K.E. Stephan, J.M. Buhmann (2010)The binormal assumption on precision-recall curves.Proceedings of the 20th International Conference on Pattern Recognition (ICPR), 4263-4266.

Requirements: No special requirements
Platforms: Matlab
Keyword: Archive Assumption Decision Distributional Easytouse Implementation Matlab Values
Users rating: 0/10

License: Shareware Size: 10 KB
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