ROC curve model under Pareto distribution
The receiver operating characteristic (ROC) curve is a useful graph-ical tool for analyzing the performance of a binary classifier. The area under the ROC curve (AUC) is a scalar measure of the classifier's per-formance. In this note we analyze the ROC curve derived under the assumption that the class distributions follow the Pareto model. We derive the equation of the ROC curve and compute the corresponding AUC. In addition, we discuss the optimal threshold for the classifier performance. © 2016 Firuz Kamalov and Ho Hon Leung.
This article is licensed under Creative Commons License and full text is openly accessible in CUD Digital Repository. The version of the scholarly record of this article is published in Applied Mathematical Sciences (2016), accessible online through this link https://doi.org/10.12988/ams.2016.512736.
Pareto distribution, ROC
Kamalov, F., & Leung, H. H. (2016). ROC curve model under Pareto distribution. Applied Mathematical Sciences, 10(9–12), 461–466. https://doi.org/10.12988/ams.2016.512736.