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Research of SVM Applying in the Risk of Bank's Loan to Enterprises

机译:支持向量机在企业银行贷款风险中的应用研究

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this paper presents a classification based on support vector machine (SVM) to carry out comprehensive analysis of the ability of enterprises paying debt,reduce the risk of bank to provide a loan. First this paper introduces the main principle of support vector machines to establish data classification model, using historical data for classification. Then collect the financial indices of 80 enterprises in China in 2001 to create support vector machine model for the credit risk classification for banks loan to enterprise; Finally, compared with the result of classification in the traditional Logistic regression model or the BP neural network evaluation model, this paper points out that the classification based on SVM is better than the traditional model and it could improve the classification accuracy.
机译:本文提出了一种基于支持向量机(SVM)的分类方法,对企业偿债能力,降低银行提供贷款的风险进行了综合分析。本文首先介绍了支持向量机建立数据分类模型的主要原理,即使用历史数据进行分类。然后收集2001年我国80家企业的财务指标,建立支持向量机模型,进行银行对企业贷款的信用风险分类。最后,与传统的Logistic回归模型或BP神经网络评估模型的分类结果相比,本文指出基于支持向量机的分类优于传统模型,可以提高分类的准确性。

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