readme.txt

matlab 程序用来计算roc曲线面积

Receiver Operating Characteristic (ROC) Curve Tools
An ROC (Receiver Operating Characteristic) curve is a plot of the true positive rate as a function of the false positive rate of a classifier system as the score defining the decision threshold is varied. This toolkit implements some of the basic methods for constructing and processing ROC curves discussed by Fawcett [1] and Provost and Fawcett [2]. The area under the ROC curve is a reasonable performance statistic for classifier systems assuming no knowledge of the true ratio of misclassification costs. 

Downloads:
m-file to compute ROC curve (roc.m) 
m-file to compute ROC convex hull (rocch.m) 
m-file to compute area under an ROC/ROCCH curve (auroc.m) 
demo/minimal test harness (rocdemo.m) 
References:
[1] Fawcett, T., "ROC graphs : Notes and practical considerations for researchers", Technical report, HP Laboratories, MS 1143, 1501 Page Mill Road, Palo Alto CA 94304, USA, April 2004. 
[2] Provost, F. and Fawcett, T., "Robust classification for imprecise environments", Machine Learning, vol. 42, no. 3, pp. 203-231, 2001.