Abstract
Receiver operating characteristic (ROC) analysis has been widely used in two-class problems. However, in practice, three-class problems are frequently encountered, especially in the area of medicine. To evaluate the performance of three-class classifiers, researchers have proposed the volume under the three-class ROC surface (VUS) as a figure-of-merit. Unfortunately, to the best of our knowledge, however, all the existing methods suffer heavy computational loads. In this paper, to overcome such an unsatisfactory problem, we develop an efficient dynamic programming-based algorithm for unbiased estimation of the VUS and the corresponding variance. The Monte Carlo simulations verified both the unbiasedness and computing efficiency of our algorithm compared with the state-of-the-art work proposed by Waegeman and co-authors.
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