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- W124100583 abstract "A central problem in the theory of feed-forward neural networks is the determination of the number of hidden neurons. With too few neurons the network may be unable to achieve the desired accuracy, while too many neurons leads to over-fitting. In this paper we propose a modification to the standard mean square error function which will reduce the tendency to over-fit, and which can be controlled by a single scalar parameter. A new learning algorithm, which can be used to minimise this error function, is also described." @default.
- W124100583 created "2016-06-24" @default.
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- W124100583 date "1992-01-01" @default.
- W124100583 modified "2023-09-23" @default.
- W124100583 title "Curvature-Driven Smoothing in Backpropagation Neural Networks" @default.
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- W124100583 doi "https://doi.org/10.1007/978-1-4471-1833-6_8" @default.
- W124100583 hasPublicationYear "1992" @default.
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