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Title |
Using Neural Network Rule Extraction for Credit-Risk Evaluation |
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Author |
Maria Teresinha Arns Steiner, Pedro Jos? Steiner Neto, Nei Yoshihiro Soma, Tamio Shimizu, J?lio Cesar Nievola |
| Citation |
Vol. 6 No. 5 pp. 6-16 |
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Abstract |
Credit-risk evaluation is a very important management science problem in the financial analysis area. Neural Networks have received a lot of attention because of their universal approximation property. They have a high prediction accuracy rate, but it is not easy to understand how they reach their decisions. In this paper, we present a real-life credit-risk data set and analyze it by using the NeuroRule extraction technique and the WEKA software. The results were considered very satisfactory. |
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Keywords |
Neural Networks, NeuroRule extraction technique, Credit-risk. |
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