Predicting Host Preferences of Influenza A/H7N9 Viruses by Using Machine Learning Models

摘要：

　　The occurrence that human infected by a novel avian H7N9 influenza virus crossing the species barrier had caused much concerns among the public.In this study, three machine learning methods including decision tree, neural network and support vector machine were applied to distinguish whether or not a strain of avian influenza virus acquired the capability to conquer species barrier.The average accuracy of prediction models constructed by the three methods on test samples is 71.64%, demonstrating these models good early-warning effect to public health.

关键词： H7N9 machine learning decision tree back-propagation neural network support vector machine

作者: Yanan Liu Qianying Dai Le Li Zhuang Li

作者单位: College of Informatics, Huazhong Agricultural University, Wuhan, Hubei Province 430070, China;Colleg College of Informatics, Huazhong Agricultural University, Wuhan, Hubei Province 430070, China

会议类型: 国际会议

会议名称: International Conference on Computational Science and Engineering Applications(CSEA2015)2015计算机科学与工程应用国际会议

会议地点: 三亚

会议语种:英文

页码: 436-439

在线出版日期: 2015-12-26（万方平台首次上网日期，不代表论文的发表时间）