Partial AUC Maximization via Nonlinear Scoring Functions

Understand

We propose a method for maximizing a partial area under a receiver operating characteristic (ROC) curve (pAUC) for binary classification tasks.

• In binary classification tasks, accuracy is the most commonly used as a measure of classifier performance.
• In some applications such as anomaly detection and diagnostic testing, accuracy is not an appropriate measure since prior probabilties are often greatly biased.
• Although in such cases the pAUC has been utilized as a performance measure, few methods have been proposed for directly maximizing the pAUC.