A Comparison Study of Credit Scoring Models

by: Defu Zhang, Hongyi Huang, Qingshan Chen, Yi Jiang

Natural Computation, 2007. ICNC 2007. Third International Conference on, Vol. 1 (2007), pp. 15-18.

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Compares ANN, GP and SVM in the determination of credit scoring models.

GP

Details about the algorithms implementation are in the references Building credit scoring models using genetic programming and Two-stage genetic programming (2SGP) for the credit scoring problem

Experiments/Results

Uses two different datasets: German and Australian credit datasets

Reviewed by sventura - 2008-05-21 23:45:53

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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.

@inproceedings{citeulike:2443272, 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.}, author = {Zhang, Defu and Huang, Hongyi and Chen, Qingshan and Jiang, Yi }, booktitle = {Natural Computation, 2007. ICNC 2007. Third International Conference on}, citeulike-article-id = {2443272}, doi = {10.1109/ICNC.2007.15}, journal = {Natural Computation, 2007. ICNC 2007. Third International Conference on}, keywords = {creditscoring}, pages = {15--18}, posted-at = {2008-05-16 09:14:25}, priority = {2}, title = {A Comparison Study of Credit Scoring Models}, url = {http://dx.doi.org/10.1109/ICNC.2007.15}, volume = {1}, year = {2007} }

RIS record

TY - CONF ID - citeulike:2443272 L3 - citeulike-article-id:2443272 TI - A Comparison Study of Credit Scoring Models T2 - Natural Computation, 2007. ICNC 2007. Third International Conference on JF - Natural Computation, 2007. ICNC 2007. Third International Conference on VL - 1 SP - 15 EP - 18 N2 - 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. KW - creditscoring AU - Zhang, Defu AU - Huang, Hongyi AU - Chen, Qingshan AU - Jiang, Yi PY - 2007/// UR - http://dx.doi.org/10.1109/ICNC.2007.15 ER -

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