Recovery Discrimination based on Optimized-Variables Support Vector Machine for Nonperforming Loan |
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Authors: | Hao CHEN Yu-chao MA Mu-zi CHEN Yue TANG Bo WANG Min CHEN Xiao-guang YANG |
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Institution: | Academy of Mathematics and Systems Science, CAS, Beijing 100190, China |
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Abstract: | This article modifies the Support Vector Machine (SVM) algorithm to address the issue of a large number of explantory variables in the analysis of nonperforming loan recovery. First, the stepwise SVM is employed in the selection of model structure. Secondly, the results of linear stepwise regression are used as the initial states of the model selection. Empirical results show that the method not only achieves high accurate out-sample prediction, but also stable performance with in-samples and out-samples. |
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