| 基于朴素贝叶斯分类器的个人信用评估模型 |
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| 引用本文： | 李旭升,郭耀煌.基于朴素贝叶斯分类器的个人信用评估模型[J].计算机工程与应用,2006,42(30):197-201. |
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| 作者姓名： | 李旭升 郭耀煌 |
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| 作者单位： | 西南交通大学经济管理学院,成都,610031 |
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| 摘 要： | 个人信用评估是金融与银行界研究的重要内容。论文研究了三种朴素贝叶斯分类器信用评估模型的精度。在两个真实数据集上用10层交叉验证对朴素贝叶斯信用评估模型进行了测试,并与五种DavidWest的神经网络个人信用评估模型进行了对比。结果表明朴素贝叶斯分类器具有较低的分类误差,在信用评估中有优势。
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| 关 键 词： | 个人信用评估 朴素贝叶斯分类器 神经网络 10层交叉验证 |
| 文章编号： | 1002-8331（2006）30-0197-05 |
| 收稿时间： | 2006-05-01 |
| 修稿时间： | 2006-05-01 |
Personal Credit Scoring Models on Naive Bayesian Classifier |
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| LI Xu-sheng,GUO Yao-huang.Personal Credit Scoring Models on Naive Bayesian Classifier[J].Computer Engineering and Applications,2006,42(30):197-201. |
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| Authors: | LI Xu-sheng GUO Yao-huang |
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| Affiliation: | School of Economics and Management,Southwest JiaoTong University, Chengdu 610031 |
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| Abstract: | Personal credit scoring plays an important role in financial and banking industry.This paper investigates the credit scoring accuracy of three naive Bayesian classifier models.They are tested using 10-fold cross validation with two real world data sets,and compared with five neural network models of David West's.Results demonstrate that the naive Bayesian classifiers are competitive with neural network classifiers and predominant in credit scoring domain. |
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| Keywords: | personal credit scoring naive Bayesian classifier Neural network 10-fold cross validation |
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