Individual Credit Risk Assessment Model Based on Rough Set and Support Vector Machines

Shangfeng Yao

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Individual Credit Risk Assessment Model Based on Rough Set and Support Vector Machines

机译：基于粗糙集和支持向量机的个人信用风险评估模型

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摘要

Individual credit risk assessment model is constructed based on rough sets and support vector machines in order to achieve better prediction classification ability; by empirical analysis and comparison with the SVM method, linear discriminant analysis, logistic regression analysis, k-nearest neighbor estimation, classification and regression tree, neural network and PCA-NN, the our results show that the method has good prediction.

机译：基于粗糙集和支持向量机构建个人信用风险评估模型，以达到更好的预测分类能力。通过与SVM方法，线性判别分析，逻辑回归分析，k最近邻估计，分类和回归树，神经网络和PCA-NN的经验分析和比较，我们的结果表明该方法具有良好的预测能力。

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来源
《Journal of systems science & information》 |2010年第2期|P.149-156|共8页
作者
Shangfeng Yao;
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作者单位

Section of Mathematics and Physics, Bengbu Tank Institute, Bengbu 233050, China;

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原文格式 PDF
正文语种 eng
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关键词
credit risk; credit risk assessment; rough set; support vector machine; 5; fold cross-validation;

机译：信用风险;信用风险评估;粗糙集支持向量机5;交叉验证;

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4. The Integrated Methodology of Rough Set Theory and Support Vector Machine for Credit Risk Assessment [C] . Jianguo Zhou, Zhaoming Wu, Chenguang Yang, . 2006

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5. Support vector parameter selection using experimental design based generating set search (SVEG) with application to predictive software data modeling. [D] . Lim, Hojung. 2004

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6. Modeling Mode Choice Behavior Incorporating Household and Individual Sociodemographics and Travel Attributes Based on Rough Sets Theory [O] . Long Cheng, Xuewu Chen, Ming Wei, 2014

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7. Credit risk assessment based on rough set theory and fuzzy support vector machine [O] . Jianguo Zhou, Jiming Tian 2007

机译：基于粗糙集理论和模糊支持向量机的信用风险评估

Individual Credit Risk Assessment Model Based on Rough Set and Support Vector Machines

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