Boosting the Area under the ROC Curve

Part of Advances in Neural Information Processing Systems 20 (NIPS 2007)

Bibtex Metadata Paper Supplemental

Authors

Phil Long, Rocco Servedio

Abstract

We show that any weak ranker that can achieve an area under the ROC curve slightly better than 1/2 (which can be achieved by random guessing) can be effi- ciently boosted to achieve an area under the ROC curve arbitrarily close to 1. We further show that this boosting can be performed even in the presence of indepen- dent misclassification noise, given access to a noise-tolerant weak ranker.