PAV and the ROC convex hull

Classifier calibration is the process of converting classifier scores into reliable probability estimates. Recently, a calibration technique based on isotonic regression has gained attention within machine learning as a flexible and effective way to calibrate classifiers. We show that, surprisingly, isotonic regression based calibration using the Pool Adjacent Violators algorithm is equivalent to the ROC convex hull method.

• Type: Journal
• Year: 2007
• Where: ML
• Authors: Tom Fawcett, Alexandru Niculescu-Mizil
• Keywords: Calibration, Isotonic Regression, Machine Learning, ML 2007, Regression Based Calibration