AN EFFICIENT LEARNING ALGORITHM OF NONBALANCED TRAINING SET FOR BP NETWORK

Jiang Minghu; Lin Biqin; Yuan Baozong; Xu Xiaobin

Volume 21 Issue 3

May 1999

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Article Navigation > Journal of Electronics & Information Technology > 1999 > 21(3): 412-415

Jiang Minghu, Lin Biqin, Yuan Baozong, Xu Xiaobin. AN EFFICIENT LEARNING ALGORITHM OF NONBALANCED TRAINING SET FOR BP NETWORK[J]. Journal of Electronics & Information Technology, 1999, 21(3): 412-415.

Citation:

Jiang Minghu, Lin Biqin, Yuan Baozong, Xu Xiaobin. AN EFFICIENT LEARNING ALGORITHM OF NONBALANCED TRAINING SET FOR BP NETWORK[J]. Journal of Electronics & Information Technology, 1999, 21(3): 412-415.

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AN EFFICIENT LEARNING ALGORITHM OF NONBALANCED TRAINING SET FOR BP NETWORK

Received Date: 1997-10-22
Rev Recd Date: 1998-06-26
Publish Date: 1999-05-19

Abstract

Abstract

This paper analyzes the reason for low convergence rate of BP network standard backpropagation algorithm to nonblanced training set, researches how to improve the learning algorithm in order to increase training speed, and through two experiments tests and verifies above theory.

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References(1)

References

Anand R,et al. Efficient classification for multiclass problem using modular neural networks. IEEE Trans. on Neural Networks, 1995, NN-6(1): 117-124.[2]Anand R, et al. An improved algorithm for neural networks classification of imbalanced training sets. IEEE Trans. on Neural Networks, 1993, NN-4(6): 962-969.[3]Waibel A, et al. Modularity and scaling in large phonemic neural networks. IEEE Trans. on ASSP, 1989, ASSP-37(12): 1888-1898.[4]Waibel A, et al. Phoneme recognition using time-delay neural networks. IEEE Trans. on ASSP, 1989, ASSP-37(3): 328-339.

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