An efficient and user-friendly software tool for ordered multi-class receiver operating characteristic analysis based on python
Shun Liu,
Junjie Yang,
Xianxian Zeng,
Haiying Song,
Jian Cen,
Weichao Xu
Affiliations
Shun Liu
Department of Automatic Control, School of Automation, Guangdong Polytechnic Normal University, Guangzhou, 510650, China; Guangzhou Intelligent Building Equipment Information Integration and Control Key Laboratory, Guangzhou 510665, China
Junjie Yang
Université Paris Saclay, CNRS, CentraleSupelec, Laboratoire des Signaux et Système UMR 8506, Plateau du Moulon, 3 Rue Joliot Curie, Gif sur Yvette, France; Corresponding author.
Xianxian Zeng
School of Computer and Science, Guangdong Polytechnic Normal University, Guangzhou, 510650, China
Haiying Song
Department of Automatic Control, School of Automation, Guangdong Polytechnic Normal University, Guangzhou, 510650, China; Guangzhou Intelligent Building Equipment Information Integration and Control Key Laboratory, Guangzhou 510665, China
Jian Cen
Department of Automatic Control, School of Automation, Guangdong Polytechnic Normal University, Guangzhou, 510650, China; Guangzhou Intelligent Building Equipment Information Integration and Control Key Laboratory, Guangzhou 510665, China
Weichao Xu
School of Automation, Guangdong University of Technology, 510006, Guangzhou, China
Receiver Operating Characteristic (ROC) analysis is a prevalent tool for two-class problems in a wide range of science and engineering areas. The relevant scalar area under the ROC curve (AUC) has been proven to be a robust evaluation index for characterizing the performance of binary statistical models. However, tasks with more than two categories are frequently encountered in practice. As an extension of the ROC curve and AUC in parallel, the hyper ROC surface and the corresponding hyper-volume under the surface (HVUS) have attracted extensive interest. The current mainstream analysis tools of AUC and HVUS are based on the R program language. To provide researchers with an alternative tool for multi-class ROC analysis, in this work, we develop a python-based package and software tool, which allows the users to unbiasedly estimate HVUS, confidently compare HVUSs, and flexibly visualize 2D-ROC curve and 3D-ROC surface, etc.
