Journal
MACHINE LEARNING
Volume 68, Issue 1, Pages 97-106Publisher
SPRINGER
DOI: 10.1007/s10994-007-5011-0
Keywords
classification; classifier calibration; ROC; class skew
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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.
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