SVM-based Credit Rating and Feature Selection

被引：1

作者：

Qin, Yu-qiang ^{[1
,2
]}

Qi, Yu-dong ^{[1
]}

Ying, Hui ^{[3
]}

机构：

[1] Capital Univ Econ & Business, Coll Business Adm, Beijing 100070, Peoples R China

[2] Taiyuan Univ Sci & Technol, Coll Econ & Management, Taiyuan 030024, Shanxi, Peoples R China

[3] Taiyuan Normal Univ, Taiyuan, Peoples R China

来源：

MATERIALS, MACHINES AND DEVELOPMENT OF TECHNOLOGIES FOR INDUSTRIAL PRODUCTION | 2014年 / 618卷

关键词：

SVM; Credit rating; Feature selection; SUPPORT VECTOR MACHINES; CLASSIFICATION;

D O I：

10.4028/www.scientific.net/AMM.618.573

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

The assessment of risk of default on credit is important for financial institutions. Logistic regression and discriminant analysis are techniques traditionally used in credit rating for determining likelihood to default based on consumer application and credit reference agency data. We test support vector machines(SVM) against these traditional methods on a large credit card database. We find that they are competitive and can be used as the basis of a feature selection method to discover those features that are most significant in determining risk of default.

引用

页码：573 / +

页数：2

共 50 条

[21] SVM-Based Feature Selection for Differential Space Fusion and Its Application to Diabetic Fundus Image Classification [J].

Ding, Weiping .

IEEE ACCESS, 2019, 7 :149493-149502

[22] Use of SVM-based ensemble feature selection method for gene expression data analysis [J].

Zhang, Shizhi ;

Zhang, Mingjin .

STATISTICAL APPLICATIONS IN GENETICS AND MOLECULAR BIOLOGY, 2022, 21 (01)

[23] Feature selection algorithm based on SVM [J].

Sun Jiongjiong ;

Liu Jun ;

Wei Xuguang .

PROCEEDINGS OF THE 35TH CHINESE CONTROL CONFERENCE 2016, 2016, :4113-4116

[24] Semi-supervised SVM-based Feature Selection for Cancer Classification using Microarray Gene Expression Data [J].

Ang, Jun Chin ;

Haron, Habibollah ;

Hamed, Haza Nuzly Abdull .

CURRENT APPROACHES IN APPLIED ARTIFICIAL INTELLIGENCE, 2015, 9101 :468-477

[25] An Efficient SVM-Based Feature Selection Model for Cancer Classification Using High-Dimensional Microarray Data [J].

El Kafrawy, Passent ;

Fathi, Hanaa ;

Qaraad, Mohammed ;

Kelany, Ayda K. ;

Chen, Xumin .

IEEE ACCESS, 2021, 9 :155353-155369

[26] Feature extraction and normalization in SVM-based speaker recognition [J].

Mazibuko, Thembisile ;

Mashao, Daniel .

WMSCI 2006: 10TH WORLD MULTI-CONFERENCE ON SYSTEMICS, CYBERNETICS AND INFORMATICS, VOL V, PROCEEDINGS, 2006, :260-+

[27] SVM-based face recognition using genetic search for Frequency-Feature Subset selection [J].

Amine, Aouatif ;

Rziza, Mohammed ;

Aboutajdine, Driss .

IMAGE AND SIGNAL PROCESSING, 2008, 5099 :321-328

[28] SVM-based local search for gene selection and classification of microarray data [J].

Hernandez, Jose Crispin Hernandez ;

Duval, Beatrice ;

Hao, Jin-Kao .

BIOINFORMATICS RESEARCH AND DEVELOPMENT, PROCEEDINGS, 2008, 13 :499-508

[29] The Research on Credit Rating Evaluation Based on SVM and BNN [J].

Li, Yongchen ;

Xu, Honge .

ADVANCES IN BUSINESS INTELLIGENCE AND FINANCIAL ENGINEERING, 2008, 5 :439-443

[30] SVM-Based Swift Trust Rating Model in E-commerce. [J].

Chen, Jie ;

Xu, Guangquan .

PROCEEDINGS OF THE FIRST INTERNATIONAL WORKSHOP ON EDUCATION TECHNOLOGY AND COMPUTER SCIENCE, VOL I, 2009, :640-+

← 1 2 3 4 5 →