国内大数据挖掘技术svm在信用风险评估中的应用研究综述

Mu Zhang, L. Pang
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引用次数: 2

摘要

支持向量机(SVM)作为大数据挖掘技术中的一种分类模型,经过不断的发展和完善,在信用风险领域得到了越来越广泛的应用。利用支持向量机对信用风险进行有效的评估,有利于银行和企业的发展。本文主要从支持向量机在信用风险评估中的数据预处理、应用与改进、集成组合判别三个方面对国内文献进行梳理。最后,对国内相关文献进行了简要的回顾。通过对所评审期刊的整理,可以更好地了解支持向量机在信用风险领域的具体应用现状,为后续的研究工作奠定基础。关键词:大数据挖掘技术;支持向量机;信用风险;信用风险评估;期刊了
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Review of Domestic Application Research of Big Data Mining Technology-SVM in Credit Risk Evaluation
As a classification model in large data mining technology, support vector machine (SVM) has been developing and improving continuously, it has been applied to the field of credit risk more and more widely. The effective evaluation of credit risk by support vector machine is beneficial to the development of banks and enterprises. This paper mainly combs the domestic literature from three aspects: data preprocessing, application and improvement, and integrated combination discrimination of support vector machine in credit risk assessment. Finally, a brief review based on the domestic literature is made. Through the collation of journals reviewed, we can better understand the specific application status of support vector machine in the field of credit risk and lay the foundation for the follow-up research work. Keywords—big data mining technology; support vector machine; credit risk; credit risk Evaluation; Journals reviewed
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