A new method to evaluate a trained artificial neural network
Date
2001-01-01
Advisors
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ISSN
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Type
Other
Peer reviewed
Abstract
Description
It is possible for a trained neural network to give a false mapping. We propose 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. In this way, the available data could be fully applied to the training stage and the validation is simple and efficient.
Keywords
RAE 2008, UoA 23 Computer Science and Informatics, neural nets
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