Boosting the area under the ROC curve

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.

• Machine intelligence