Ensemble of SVMs for incremental learning

Lecture Notes in Computer Science

Volumn 3541, Issue , 2005, Pages 246-256

  Erdem, Zeki ^a,d   Polikar, Robi ^b   Gurgen, Fikret ^c   Yumusak, Nejat ^d  

^a MATERIALS INSTITUTE   (Turkey)

^b Rowan University   (United States)

^c BOGAZICI UNIVERSITY   (Turkey)

^d SAKARYA UNIVERSITY   (Turkey)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; KNOWLEDGE ACQUISITION; LEARNING ALGORITHMS; PROBLEM SOLVING; REGRESSION ANALYSIS; VECTORS;

BENCHMARK DATASETS; CATASTROPHIC FORGETTING PROBLEM; REGRESSION PROBLEMS; SUPPORT VECTOR MACHINES (SVM);

LEARNING SYSTEMS;

EID: 26444461220     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/11494683_25     Document Type: Conference Paper

References (20)

1. V. Vapnik, Statistical Learning Theory. New York: Wiley, 1998.
2. N. Cristianini, J. Shawe-Taylor, An Introduction to Support Vector Machines and Other Kernel-based Learning Methods, Cambridge University Press, 2000.
3. S. Grossberg, "Nonlinear neural networks: principles, mechanisms and architectures," Neural Networks, Vol. 1, No. 1, pp. 17-61, 1988.
4. R. French, "Catastrophic forgetting in connectionist networks: Causes, Consequences and Solutions," Trends in Cognitive Sciences, vol. 3, no.4, pp. 128-135, 1999.
5. ++: An incremental learning algorithm for multilayer perceptrons." Proceedings of 25th. IEEE International Conference on Acoustics, Speech and Signal Processing, Vol. 6, pp: 3414-3417, Istanbul, Turkey, 2000.
6. ++: An incremental learning algorithm for supervised neural networks." IEEE Transactions on Systems, Man, and Cybernetics. Part C: Applications and Reviews, Vol. 31, No. 4, pp: 497-508, 2001.
7. Y. Freund, R. Schapire, "A decision theoretic generalization of on-line learning and an application to boosting," Computer and System Sciences, vol. 57, no. 1, pp. 119-139, 1997.
8. N. Kasabov, "Evolving Connectionist Systems: Methods and Applications in Bioinformatics, Brain Study and Intelligent Machines", Springer Verlag, 2002.
9. J. Platt, "Fast Training of Support Vector Machines using Sequential Minimal Optimization", Advances in Kernel Methods - Support Vector Learning, B. Schölkopf, C. Burges, and A. Smola, eds., MIT Press, 1998.
10. C. Domeniconi, D. Gunopulos, "Incremental Support Machine Construction", Proceedings of First IEEE Int. Conf. on Data Mining (ICDM 2001), pp. 589-592.
11. P. Mitra, C.A. Murthy, S.K. Pal, "Data condensation in large databases by incremental learning with support vector machines", Proceedings of 15th International Conference on Pattern Recognition, Vol.2, pp:708 - 711, 3-7 Sept 2000.
12. K. Li, H.-K. Huang, "Incremental learning proximal support vector machine classifiers", Proceedings of International Conference on Machine Learning and Cybernetics, vol. 3, pp: 1635-1637, 4-5 November 2002.
13. J.-L. An, Z.-O. Wang, Z.-P. Ma, "An incremental learning algorithm for support vector machine", Proceedings of International Conference on Machine Learning and Cybernetics, Vol.2, pp:1153 - 1156, 2-5 November 2003.
14. Z.-W. Li; J.-P. Zhang, J. Yang, "A heuristic algorithm to incremental support vector machine learning", Proceedings of 2004 International Conference on Machine Learning and Cybernetics, Vol. 3, pp: 1764-1767, 26-29 Aug. 2004.
15. D. Pavlov, J. Mao, and B. Dom, Scaling-up Support Vector Machines using The Boosting Algorithm, Proceedings of the International Conference on Pattern Recognition, Barcelona, Spain, September 3-7 2000, pp. 19-22.
16. G. Valentini, M. Muselli, and F. Ruffino, Cancer Recognition with Bagged Ensembles of Support Vector Machines, Neurocomputing 56(1), (2004), pp. 461-466.
17. G. Valentini, M. Muselli, F. Ruffino, Bagged Ensembles of SVMs for Gene Expression Data Analysis, Proceeding of the International Joint Conference on Neural Networks, Portland, OR, USA, July 20-24 2003, pp. 1844-1849.
18. H.-C. Kim, S. Pang, H.-M. Je, D. Kim, and S. Y. Bang, Constructing Support Vector Machine Ensemble, Pattern Recognition 36, (2003), pp. 2757-2767.
19. K. Duan, S.S. Keerthi, A.N. Poo, Evaluation of simple performance measures for tuning SVM hyperparameters, Neurocomputing, 51 (2003) 41-59.
20. ++.MT: A New Approach to Incremental Learning, 5th Int. Workshop on Multiple Classifier Systems (MCS 2004), Springer LINS vol. 3077, pp. 52-61, Cagliari, Italy, June 2004.