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11 January 2005 Study on evaluation ways of feed-forward neural networks generalization ability
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Abstract
Generalization ability of feed-forward neural networks is discussed in this paper. Firstly, presents and certifies two practical methods for improving networks generalization ability based on theory and experiment research. Secondly, gives a measuring model of networks generalization ability with generalization error. The essential is to define a probability input model and regard the expectation error of network upon testing samples as index for measuring networks generalization ability. Computation quantity and complexity are much less compared with traditional method.
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Yanfang Li, Wei He, and Huamin Yang "Study on evaluation ways of feed-forward neural networks generalization ability", Proc. SPIE 5642, Information Optics and Photonics Technology, (11 January 2005); https://doi.org/10.1117/12.574709
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