A Case-Based Reasoning Method with Rank Aggregation

摘要：

　　In order to improve the accuracy of case-based reasoning(CBR),this paper addresses a new CBR framework with the basic principle of rank aggregation.First,the ranking methods are put forward in each attribute subspace of case.The ordering relation between cases on each attribute is got between cases.Then,a sorting matrix is got.Second,the similar case retrieval process from ranking matrix is transformed into a rank aggregation optimal problem,which uses the Kemeny optimal.On the basis,a rank aggregation case-based reasoning algorithm,named RA-CBR,is designed.The experiment result on UCI data sets shows that case retrieval accuracy of RA-CBR algorithm is higher than euclidean distance CBR and mahalanobis distance CBR testing.So we can get the conclusion that RA-CBR method can increase the performance and efficiency of CBR.

作者: Jinhua Sun Jiao Du Jian Hu

作者单位: School of Management,Chongqing University of Technology,Chongqing,China

会议类型: 国际会议

会议名称: The 1st International Symposium on Application of Materials Science and Energy Materials (SAMSE 2017)

会议地点: 上海

会议语种:英文

页码: 1-7

在线出版日期: 2017-12-28（万方平台首次上网日期，不代表论文的发表时间）