A Theoretical Study of the Generalization Ability of Feed-forward Neural Networks
نویسنده
چکیده
By making assumptions on the probability distribution of the potentials in a feed-forward neural network we have derived lower bounds for the generalization ability of the network in terms of the number of training patterns. The results are consistent with simulations carried out on a simple geometrical function.
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