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|Title: ||A new method to evaluate a trained artificial neural network|
|Authors: ||Yang, Yingjie|
Hinde, Chris J.
|Keywords: ||Neural nets|
|Issue Date: ||2001|
|Publisher: ||© IEEE|
|Citation: ||YANG, Y., HINDE, C.J. and GILLINGWATER, D., 2001. A new method to evaluate a trained artificial neural network. IN: Proceedings. IJCNN '01. International Joint Conference Neural Networks, Washington, DC, 15-19 July, Vol.4, pp. 2620-2625|
|Abstract: ||In comparison with traditional local sample testing methods, this paper proposes a new approach to evaluate a trained neural network. A new parameter is defined to identify the different potential roles of the individual input factors based on the trained connections of the nodes in the network. Compared with field-specific knowledge, the dominance of individual input factors can be checked and then false mappings satisfying only the specific data set may be avoided.|
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|Appears in Collections:||Conference Papers (Computer Science)|
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