Classification error of multilayer perceptron neural networks |
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Authors: | Lihua Feng Weihu Hong |
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Affiliation: | (1) Department of Geography, Zhejiang Normal University, No. 688 Yingbin Road, Jinhua, 321004, China;(2) Department of Mathematics, Clayton State University, Morrow, GA 30260, USA |
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Abstract: | In subject classification, artificial neural networks (ANNS) are efficient and objective classification methods. Thus, they have been successfully applied to the numerous classification fields. Sometimes, however, classifications do not match the real world, and are subjected to errors. These problems are caused by the nature of ANNS. We discuss these on multilayer perceptron neural networks. By studying of these problems, it helps us to have a better understanding on its classification. |
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Keywords: | Artificial neural networks Multilayer perceptron neural networks Subject Class Classification Error |
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