Receiver operating characteristic for diagnosis of wine quality by Bayesian network classifiers

摘要：

　　This paper is dedicated to demonstrate the use of the receiver operating characteristic (ROC) and the area under the ROC curve (AUC) for diagnosing forecast skill.Several local search heuristic algorithms to discover which one performs better for learning a certain Bayesian networks (BN).Five heuristic search algorithms,including K2,Hill Climbing,Repeated Hill Climber,LAGD Hill Climbing,and TAN,were empirically evaluated and compared.This study tests BN models in a real-world case,the Vinho Verde wine taste preferences.An average AUC of 0.746 and 0.727respectively in red wine and white wine were obtained by TAN algorithm.The results show that the use of TAN can effectively improve the AUC measures for predicting quality grade.

关键词： Receiver operating characteristic Bayesian networks Classification

作者: Chih-Chiang Wei

作者单位: Department of Information Management,Toko University.No.51,Sec.2,University Rd.,Pu-Tzu City,Chia-Yi County 61363,Taiwan

会议类型: 国际会议

会议名称: the 2012 International Conference on Manufacturing Engineering and Automation (2012年制造工程与自动化国际会议(ICMEA2012))

会议地点: 广州

会议语种:英文

页码: 1168-1173

在线出版日期: 2012-11-16（万方平台首次上网日期，不代表论文的发表时间）