| 信用评估中的鲁棒赋权自适应Lp最小二乘支持向量机方法 |
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| 引用本文： | 刘京礼,李建平,徐伟宣,石勇. 信用评估中的鲁棒赋权自适应Lp最小二乘支持向量机方法[J]. 中国管理科学, 2010, 18(5): 28-33 |
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| 作者姓名： | 刘京礼 李建平 徐伟宣 石勇 |
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| 作者单位： | 1. 中国科学技术大学管理学院, 安徽 合肥 230026;2. 中国科学院科技政策与管理科学研究所, 北京 100190;3. 中国科学院虚拟经济与数据科学研究中心, 北京 100190 |
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| 基金项目： | 国家自然科学基金资助项目(70531040,70621001,70921061) |
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| 摘 要： | 消费者信用评估是金融风险管理和信用产业竞争的一个重要方面.信用评估数据中常带有噪声点,并且其类别是不均衡的.最小二乘支持向量机是一个被广泛应用的分类模型,其模型简单,求解速度快,但鲁棒性差.本文提出了一个鲁棒赋权自适应Lp最小二乘支持向量机模型,能够适应信用评估样本数据库类别不均衡的特点,可以有效处理信用评估数据中带有噪声点的问题.在仿真数据和三个信用数据库上的实证分析表明,本文所提出的模型具有较好的鲁棒性和分类能力.
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| 关 键 词： | 信用评估 鲁棒 自适应 最小二乘支持向量机 |
| 收稿时间： | 2009-11-07 |
| 修稿时间： | 2010-07-12 |
A Robust Weighted Adaptive Lp LS-SVM Method for Credit Risk Assessment |
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| LIU Jing-li,LI Jian-ping,XU Wei-xuan,SHI Yong. A Robust Weighted Adaptive Lp LS-SVM Method for Credit Risk Assessment[J]. Chinese Journal of Management Science, 2010, 18(5): 28-33 |
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| Authors: | LIU Jing-li LI Jian-ping XU Wei-xuan SHI Yong |
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| Affiliation: | 1. School of Management, University of Science and Technology of China, Hefei 230026, China;2. Institute of Policy and Management, Chinese Academy of Sciences, Beijing 100190, China;3. Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing 100190, China |
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| Abstract: | Consumer credit risk assessment is an important aspect of financial risk management and credit industry competition.Credit database often contains noisy data,which makes the data uncertain.Least squares support vector machines,a widely used binary classification model,is simple and easy to be applied.In this paper,we propose a robust weighted adaptive Lp least squares support vector machines,which can deal with unbalanced data sets and noisy data.The empirical test on simulation and three credit data sets have shown the model has out standing robustness and generalization ability. |
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| Keywords: | credit risk assessment robust adaptive least squares support vector machines |
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