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Evaluation of an anti-regularization technique in neural networks

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5 Author(s)
Hamamoto, Y. ; Fac. of Eng., Yamaguchi Univ., Ube, Japan ; Mitani, Y. ; Ishihara, H. ; Hase, T.
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An anti-regularization technique which has been recently proposed by Raudys (1995) is studied in small training sample size situations. Experimental results show that as long as the weights of a network are initialized in a very narrow interval, the anti-regularization technique offers significant advantages in terms of both the generalization ability and learning time

Published in:

Pattern Recognition, 1996., Proceedings of the 13th International Conference on  (Volume:4 )

Date of Conference:

25-29 Aug 1996

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