{"title":"Enterprise Credit Rating Model Based on Fuzzy Clustering and Decision Tree","authors":"Wu Hongxia, L. Xueqin, Liu Yanhui","doi":"10.1109/ISISE.2010.25","DOIUrl":null,"url":null,"abstract":"In order to assess enterprise credit rating objectively and fairly, this paper focuses on how to combine the Data Ming with assessing enterprise credit rating. Firstly the comprehensive evaluation index system of enterprise credit rating is built up. Then the comprehensive evaluation method of the credit rating of enterprise is put forward based on the decision tree and fuzzy clustering algorithm. Applying the method proposed to assessing the credit rating of enterprise shows that the management level and employee quality is the most important factors.","PeriodicalId":206833,"journal":{"name":"2010 Third International Symposium on Information Science and Engineering","volume":"87 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Third International Symposium on Information Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISISE.2010.25","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
In order to assess enterprise credit rating objectively and fairly, this paper focuses on how to combine the Data Ming with assessing enterprise credit rating. Firstly the comprehensive evaluation index system of enterprise credit rating is built up. Then the comprehensive evaluation method of the credit rating of enterprise is put forward based on the decision tree and fuzzy clustering algorithm. Applying the method proposed to assessing the credit rating of enterprise shows that the management level and employee quality is the most important factors.