Abstract
The selection of evaluating index system is the key to personal credit scoring, which is a feature selection problem.By improving the typical SVM based on 1-norm, which can select the important and necessary feature of samples, an improved SVM based on 1-norm adapted to the selection of personal credit scoring index system is proposed. Experimental results shows that the new improved method can select evaluating index system with small scale and enhance the generality ability and reduce the arithmetic complexity of the classification machine.
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Xue, X., He, G. (2007). An Improved SVM Based on 1-Norm for Selection of Personal Credit Scoring Index System. In: Liu, D., Fei, S., Hou, Z., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4493. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72395-0_56
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DOI: https://doi.org/10.1007/978-3-540-72395-0_56
Publisher Name: Springer, Berlin, Heidelberg
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