A faster learning neural network classifier using selective backpropagation
The problem of saturation in neural network classification problems is discussed. The listprop algorithm is presented which reduces saturation and dramatically increases the rate of convergence. The technique uses selective application of the backpropagation algorithm, such that training is only...
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| Format: | Conference or Workshop Item |
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1997
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| Online Access: | https://eprints.nottingham.ac.uk/1901/ |