A Preliminary Study on Negative Correlation Learning via Correlation-Corrected Data (NCCD)

1. R. T. Clemen R. L. Winkler (1985) ArticleTitleLimits for the precision and value of information from dependent sources Operation Research 33 427–442

   Google Scholar 

2. M. Perrone L. N. Cooper (1993) When networks disagree: ensemble methods for hybrid neural networks R. J. Mammone (Eds) Neural Networks for Speech and Image Processing Chapman & Hall London, U.K

   Google Scholar 

3. Y. Liu X. Yao (1999) ArticleTitleSimultaneous training of negatively correlated neural networks in an ensemble IEEE Transactions on Systems, Man and Cybernetics-Part B: Cybernetics 29 716–725

   Google Scholar 

4. Yao, X. and Liu, Y.: A new evolutionary system for evolving artificial neural networks, IEEE Transactions on Neural Networks 8 (May 1997), 694–713

   Google Scholar 

5. Crowder, R. S.: Predicting the Mackey–Glass time series with cascade-correlation learning, In D. S. T. (ed.), Connectionist Models: Proceedings of the 990 Connectionist Models Summer School, pp. 117–123, 1990

6. X. Yao Y. Liu (1998) ArticleTitleMaking use of population information in evolutionary artificial neural networks IEEE Transactions on Systems, Man and Cybernetics-Part B: Cybernetics 28 417–425

   Google Scholar 

7. D. Michie D. J. Spiegelhalter C. C. Taylor (1994) Machine Learning, Neural and Statistical Classification Ellis Horwood London, U.K

   Google Scholar 

8. M. Islam X. Yao K. Murase (2003) ArticleTitleA constructive algorithm for training cooperative neural network ensembles IEEE Transactions on Neural Networks 14 820–834

   Google Scholar 

9. C. Bishop (1995) Neural Networks for Pattern Recognition Oxford University Press Inc. oxford

   Google Scholar 

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