Designing classifier fusion systems by genetic algorithms

IEEE Transactions on Evolutionary Computation

Volumn 4, Issue 4, 2000, Pages 327-336

  Kuncheva, Ludmila I ^a   Jain, Lakhmi C ^b,c  

^a BANGOR UNIVERSITY   (United Kingdom)

^b UNIVERSITY OF SOUTH AUSTRALIA   (Australia)

^c University of South Austrailia   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFIER FUSION SYSTEMS; MULTIPLE CLASSIFIERS;

ERROR ANALYSIS; FEATURE EXTRACTION; MATHEMATICAL MODELS; OPTIMIZATION; VECTORS;

GENETIC ALGORITHMS;

EID: 0034314744     PISSN: 1089778X     EISSN: None     Source Type: Journal    
DOI: 10.1109/4235.887233     Document Type: Article

References (21)

1. P. D. Gader, M. A. Mohamed, and J. M. Keller, "Fusion of handwritten word classifiers," Pattern Recognit. Lett., vol. 17, pp. 577-584, 1996.
2. J. M. Keller, P. Gader, H. Tahani, J.-H. Chiang, and M. Mohamed, "Advances in fuzzy integration for pattern recognition," Fuzzy Sets Syst., vol. 65, pp. 273-283, 1994.
3. H.-J. Kang, K. Kim, and J. H. Kim, "A framework for probabilistic combination of multiple classifiers at an abstract level," Eng. Appl. Artif. Intell., vol. 10, no. 4, pp. 379-385, 1997.
4. J. Kittler, M. Hatef, R. P. W. Duin, and J. Matas, "On combining classifiers," IEEE Trans. Pattern Anal. Machine Intell., vol. 20, no. 3, pp. 226-239, 1998.
5. L. Lam and C. Y. Suen, "Optimal combination of pattern classifiers," Pattern Recognit. Lett., vol. 16, pp. 945-954, 1995.
6. K. Woods, W. P. Kegelmeyer, and K. Bowyer, "Combination of multiple classifiers using local accuracy estimates," IEEE Trans. Pattern Anal. Machine Intell., vol. 19, pp. 405-410, 1997.
7. L. Xu, A. Krzyzak, and C. Y. Suen, "Methods of combining multiple classifiers and their application to handwriting recognition," IEEE Trans. Syst., Man, Cybern., vol. 22, pp. 418-435, 1992.
8. R. A. Jacobs, "Methods for combining experts' probability assessments," Neural Comput., vol. 7, pp. 867-888, 1995.
9. R. A. Jacobs, M. I. Jordan, S. J. Nowlan, and G. E. Hinton, "Adaptive mixtures of local experts," Neural Comput., vol. 3, pp. 79-87, 1991.
10. M. I. Jordan and L. Xu, "Convergence results for the EM approach to mixtures of experts architectures," Neural Networks, vol. 8, pp. 1409-14312, 1995.
11. S. J. Nowlan and G. E. Hinton, "Evaluation of adaptive mixtures of competing experts," Advances in Neural Information Processing Systems 3, pp. 774-780, 1991.
12. C. M. Bishop, Neural Networks for Pattern Recognition. Oxford: Clarendon, 1995.
13. H. Drucker, C. Cortes, L. D. Jackel, Y. LeCun, and V. Vapnik, "Boosting and other ensemble methods," Neural Comput., vol. 6, pp. 1289-1301, 1994.
14. J. A. Benediktsson, J. R. Sveinsson, J. I. Ingimundarson, H. Sigurdsson, and O. K. Ersoy, "Multistage classifiers optimized by neural networks and genetic algorithms," Nonlinear Anal., Theory, Methods Appl., vol. 30, no. 3, pp. 1323-1334, 1997.
15. J. A. Benediktsson and P. H. Swain, "Consenus theoretic classification methods," IEEE Trans. Syst., Man, Cybern., vol. 22, pp. 688-704, 1992.
16. K.-C. Ng and B. Abramson, "Consensus diagnosis: A simulation study," IEEE Trans. Syst., Man, Cybern., vol. 22, pp. 916-928, 1992.
17. R. Battiti and A. M. Colla, "Democracy in neural nets: Voting schemes for classification," Neural Networks, vol. 7, pp. 691-707, 1994.
18. E. Filippi, M. Costa, and E. Pasero, "Multy-layer perceptron ensembles for increased performance and fault-tolerance in patern recognition tasks," in IEEE Int. Conf. Neural Networks, Orlando, FL, 1994, pp. 2901-2906.
19. E. Alpaydin and M. I. Jordan, "Local linear perceptrons for classification," IEEE Trans. Neural Networks, vol. 7, no. 3, pp. 788-792, 1996.
20. E. Alpaydin, "Voting over multiple condensed nearest neighbors," Artif. Intell. Rev., vol. 11, pp. 115-132, 1997.
21. K. Chen, L. Wang, and H. Chi, "Methods of combining multiple classifiers with different features and their applications to text-independent speaker identification," Int. J. Pattern Recognit. Artif. Intell., vol. 11, no. 3, pp. 417-445, 1997.