| 基于支持向量机的小企业信用评级最适样本量的研究 |
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| 引用本文： | 徐旭初,高志,赵纳.基于支持向量机的小企业信用评级最适样本量的研究[J].淮阴师范学院学报(自然科学版),2014(1):40-43. |
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| 作者姓名： | 徐旭初 高志 赵纳 |
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| 作者单位： | 安徽财经大学金融学院,安徽蚌埠233030 |
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| 基金项目： | 教育部规划基金项目（10YJA630181） |
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| 摘 要： | 随着企业信用评级研究的深入,大多数研究者都得出支持向量机方法在企业信用评级中具有许多优势.为了探寻支持向量机模型的最适样本量,选取安徽省2007年和2008年的小企业作为样本,运用支持向量机并采用逐级调整样本量的方法探寻模型的最适样本量.
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| 关 键 词： | 信用评级 支持向量机 最适样本量 |
Study on the Optimal Sample Size of Small Business Credit Rating Based on SVM |
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| XU Xu-chu,GAO Zhi,ZHAO Na.Study on the Optimal Sample Size of Small Business Credit Rating Based on SVM[J].Journal of Huaiyin Teachers College(Natrual Science Edition),2014(1):40-43. |
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| Authors: | XU Xu-chu GAO Zhi ZHAO Na |
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| Institution: | ( College of Finance, Anhui University of Finance and Economices, Bengbu Anhui 233030, China) |
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| Abstract: | With the deeply reseach on credit rating ,most reseachers have concluded that the Support Vector Machine（SVM）has many advantages in the enterprise credit rating .In order to explore the optimum number of samples of SVM,the paper selects the small enterprises of Anhui Province in 2007 and 2008 as samlies,using the method of SVM and gradual adjustment number of samples to explore the optimum number of samples . |
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| Keywords: | credit rating SVM optimum number of samples |
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