Boosting the Area under the ROC Curve.
P. Long and R. Servedio.
20th Conference on Neural Information Processing Systems (NIPS), 2007.


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 efficiently 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 independent misclassification noise, given access to a noise-tolerant weak ranker.

Postscript or pdf.

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