Code covered by the BSD License  

Highlights from
Estimating a smooth precision-recall curve


5.0 | 2 ratings Rate this file 37 Downloads (last 30 days) File Size: 9.36 KB File ID: #29250
image thumbnail

Estimating a smooth precision-recall curve



A set of MATLAB functions for computing a smooth approximation to the precision-recall curve.

| Watch this File

File Information

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.

Required Products Statistics Toolbox
MATLAB release MATLAB 7.10 (R2010a)
Tags for This File   Please login to tag files.
Please login to add a comment or rating.
Comments and Ratings (3)
29 Nov 2012 sahbi sahboun

good works

21 Nov 2011 Pedro

Very useful. Thank you.

18 Aug 2011 AMVR  

Contact us