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The Study on Risk Rating Model of Commercial Bank Credit Based on SVM

机译:基于SVM的商业银行信用风险评级模型研究

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According to the basic theories of Logit regression analysis and support vector machine (SVM), this article involves improved binary classification combination algorithm to increase the accuracy. In addition, using financial data of listed companies to test this improved model, it shows a better way of classification. When applying this model, there are some innovations: 1. Choose optimized composite indicator as a variable through principal component analysis and get more information; 2. Introduce Logit parameter model to the quadratic to increase prediction accuracy; 3. Put forward a combination of improved Logit model with SVM to increase prediction accuracy. This paper is supported by the Industrial Safety Engineering (239010522).
机译:根据Logit回归分析和支持向量机(SVM)的基本理论,本文涉及改进的二进制分类组合算法来提高准确性。 此外,使用上市公司的财务数据来测试这种改进的模型,它显示了更好的分类方式。 应用此模型时,有一些创新:1。通过主成分分析选择优化的复合指示器作为变量,获取更多信息; 2.将Logit参数模型引入二次以提高预测精度; 3.提出改进的Logit模型的组合,SVM提高预测精度。 本文得到了工业安全工程(239010522)的支持。

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