A Comparison Study of Credit Scoring Models

Defu Zhang, Hongyi Huang, Qingshan Chen, Yi Jiang
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引用次数: 31

Abstract

In this paper we consider a credit scoring problem. We compare three powerful credit scoring models: genetic programming (GP), backpropagation neural networks (BP) and support vector machines (SVM) when applied to this problem, then we give a combined model. The results show that the combined model produces good classification results.
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信用评分模型的比较研究
本文考虑一个信用评分问题。本文比较了遗传规划(GP)、反向传播神经网络(BP)和支持向量机(SVM)三种强大的信用评分模型在此问题中的应用,并给出了一个组合模型。结果表明,该组合模型具有较好的分类效果。
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