Research on Supplier Credit Evaluation Based on Data Mining

被引:0
作者
Ping-hua YANG
Cai-xia YANG
Jie HE
机构
[1] School of Computer Engineering, Guangzhou College of South China University of Technology
关键词
Credit scoring; Data mining; Logistic model; Weights of evidence;
会议名称
2018 International Conference on Computer, Communications and Mechatronics Engineering(CCME 2018)
会议时间
2018-12-01
会议地点
中国上海
中图分类号
F274 [企业供销管理] TP311.13
学科分类号
1201
类型
摘要
Data mining method is used to clean the real data of suppliers on cost link. With its 80% random drawing as a training set, a WOE and logistic regression model is set up to distinguish the integrity supplier on the platform according to the new calculation formula of WOE for indicator variable. And using the rest 20% as test data to calculate the accuracy of this model which is as high as 96.9%. Finally, the credit score card is established according to the linear scaling relation between the WOE value and regression coefficient of each indicator variable, which can calculate supplier credit score and provide decision-making reference for the platform and users when selecting suppliers.
引用
收藏
页码:668 / 673
页数:6
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