Credit Scoring Based on the Set-Valued Identification Method
承认基于珍视集合的鉴定方法的得分作者机构：Department of MathematicsKTH Royal Institute of TechnologyStockholm 10044Sweden Key Laboratory of Systems and ControlInstitute of Systems ScienceAcademy of Mathematics and SystemsScienceChinese Academy of SciencesBeijing 100190China School of Mathernatical SciencesUniversity ofChinese Academy of SciencesBeijing 100190China Department of MathematicsKTH Rogal Institute of TechnologyStockholm 10044Sweden
出 版 物：《Journal of Systems Science & Complexity》 (系统科学与复杂性学报（英文版）)
年 卷 期：2020年第33卷第5期
页 面：1297-1309页
核心收录：
学科分类：02[经济学] 0202[经济学-应用经济学] 020208[经济学-统计学] 07[理学] 020202[经济学-区域经济学] 0714[理学-统计学（可授理学、经济学学位）] 070103[理学-概率论与数理统计] 0701[理学-数学]
基 金：supported by the National Key R&D Program of China under Grant No.2018YFA0703800 the National Natural Science Foundation of China under Grant No.61622309 the Verg Foundation(Sweden)
主 题：Credit scoring logistic regression model prediction accuracy set-valued model
摘 要：Credit scoring is one of the key problems in financial risk *** paper studies the credit scoring problem based on the set-valued identification method,which is used to explain the relation between the individual attribute vectors and classification for the credit worthy and credit worthless *** particular,system parameters are estimated by the set-valued identification algorithm based on a given recognition *** order to illustrate the efficiency of the proposed method,practical experiments are conducted for credit card applicants of Australia and credit card holders from Taiwan,*** empirical results show that the set-valued model has a higher prediction accuracy on both small and large numbers of data set compared with logistic regression ***,parameters estimated by the set-valued identification method are more stable,which provide a meaningful and logical explanation for extracting factors that influence the borrowers’credit scorings.
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