An Application of Logistic Regression in Cerebral Infraction Disease Detection Based on Association Rules with Pre-rough Classifier

摘要：

Environment, customs and health status in northwest minority areas have been studied. We found the critical factors to prevent cerebral infraction. First rough sets theory had been used to reduce the attributes, secondly association rules had been used, finally logistic regression model had been used. The model solved the shortcomings of too many rules that caused by attribute redundancy and reliability framework. The results show that the history of other cerebrovascular disease, alcohol consumption and seasonal change are the significant factors of cerebral infraction.

关键词： Association Rules Data Mining Logistic Regression Cerebral Infraction

作者: Li YANG De-sheng XU Chang-qing LI Wen-sheng TIAN

作者单位: Management College of Inner Mongolia University of Technology,Hohhot,China,010051 First Hospital Hohhot,Hohhot,China,010051

会议类型: 国际会议

会议名称: 2010 IEEE 17th International Conference on Industrial Engineering and Engineering Management(2010年IEEE第17届工业工程与工程管理国际学术会议)

会议地点: 厦门

会议语种:英文

页码: 304-306

在线出版日期: 2010-10-29（万方平台首次上网日期，不代表论文的发表时间）