Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 36, 2019 No. 6
1683-1687

Application of improved oversampling algorithm in class-imbalance credit scoring

Shao Liangshan
Zhou Yu
System Engineering Institute, Liaoning Technical University, Huludao Liaoning 125105, China
DOI: 10.19734/j.issn.1001-3695.2017.12.0798

Abstract

In view of class-imbalance in real credit scoring business of credit industry, this paper firstly determined the main evaluation indicators of credit scoring based on a comprehensive analysis of the influence factors' Fisher ratio value. Then, it chose the SMOTE based on support degree(SDSMOTE) oversampling algorithm to synthesize new samples, SVM played as the base predictor and Boosting algorithm as the framework, this paper proposed a credit scoring prediction model which associated class-imbalance with Fisher-SDSMOTE-ESBoostSVM theory. Besides, it introduced the elimination strategy to delete the synthetic sample which was not classified accurately, after that synthesized the new positive class sample again and modified the sample weight. Finally, it selected the German credit dataset in the UCI database as the experimental dataset, and F-measure value and G-mean value as evaluation standard, comparing and analyzing the prediction result of Fisher-SDSMOTE-ESBoostSVM model and others ensemble learning algorithm. Experimental results show that the application of Fisher-SDSMOTE-ESBoostSVM algorithm to customer credit score prediction is feasible and applicable, and show a high level of accuracy, which proved that the algorithm has a certain practical application value.

Foundation Support

国家自然科学基金资助项目(71371091)
辽宁省社会规划项目(L14BTJ004)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2017.12.0798
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 6
Section: Algorithm Research & Explore
Pages: 1683-1687
Serial Number: 1001-3695(2019)06-018-1683-05

Publish History

[2019-06-05] Printed Article

Cite This Article

邵良杉, 周玉. 一种改进过采样算法在类别不平衡信用评分中的应用 [J]. 计算机应用研究, 2019, 36 (6): 1683-1687. (Shao Liangshan, Zhou Yu. Application of improved oversampling algorithm in class-imbalance credit scoring [J]. Application Research of Computers, 2019, 36 (6): 1683-1687. )

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  • Application Research of Computers Monthly Journal
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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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