Boosting the Area under the ROC Curve

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

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Phil Long, Rocco Servedio


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.