How to generate different neural networks

Studies in Computational Intelligence

Volumn 35, Issue , 2006, Pages 225-240

  Liu, Yong ^a  

^a UNIVERSITY OF AIZU   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 33750979296     PISSN: 1860949X     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-540-36122-0_9     Document Type: Article

References (16)

1. M. Stone. Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society, 36:111-147, 1974.
2. R. Meir. Bias, variance, and the combination of least squares estimators. In G. Tesauro, D. S. Touretzky, and T. K. Leen, editors, Advances in Neural Information Processing Systems 7, pages 295-302. The MIT Press, 1995.
3. B. Efron and R. J. Tibshirani. An Introduction to the Bootstrap. Chapman & Hall, 1993.
4. L. Breiman. Bagging predictors. Machine Learning, 24:123-140, 1996.
5. M. P. Perrone and L. N. Cooper. When networks disagree: Ensemble methods for hybrid neural networks. In R. J. Mammone, editor, Neural Networks for Speech and Image Processing. Chapman-Hall, London, 1993.
6. D. W. Opitz and J. W. Shavlik. Actively searching for an effective neural network ensemble. Connection Science, 8:337-353, 1996.
7. B. E. Rosen. Ensemble learning using decorrelated neural networks. Connection Science, 8:373-383, 1996.
8. Y. Liu and X. Yao. Negatively correlated neural networks can produce best ensembles. Australian Journal of Intelligent Information Processing Systems, 4:176-185, 1998.
9. Y. Liu and X. Yao. A cooperative ensemble learning system. In Proc. of the 1998 IEEE International Joint Conference on Neural Networks (IJCNN'98), pages 2202-2207. IEEE Press, Piscataway, NJ, USA, 1998.
10. Y. Liu and X. Yao. Simultaneous training of negatively correlated neural networks in an ensemble. IEEE Trans. on Systems, Man, and Cybernetics, Part B: Cybernetics, 29(6):716-725, 1999.
11. Y. Liu, X. Yao, and T. Higuchi. Evolutionary ensembles with negative correlation learning. IEEE Transactions on Evolutionary Computation, 4(4):380-387, 2000.
12. L. K. Hansen and P. Salamon. Neural network ensembles. IEEE Trans. on Pattern Analysis and Machine Intelligence, 12(10):993-1001, 1990.
13. A. J. C. Sharkey. On combining artificial neural nets. Connection Science, 8:299-313, 1996.
14. X. Yao and Y. Liu. Making use of population information in evolutionary artificial neural networks. IEEE Trans. on Systems, Man, and Cybernetics, Part B: Cybernetics, 28(3):417-425, 1998.
15. D. E. Rumelhart, G. E. Hinton, and R. J. Williams. Learning internal representations by error propagation. In D. E. Rumelhart and J. L. McClelland, editors, Parallel Distributed Processing: Explorations in the Microstructures of Cognition, Vol. I, pages 318-362. MIT Press, Cambridge, MA, 1986.
16. X. Yao and Y. Liu. A new evolutionary system for evolving artificial neural networks. IEEE Trans. on Neural Networks, 8(3):694-713, 1997.