Support vector machine classification based on fuzzy clustering for large data sets

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4293 LNAI, Issue , 2006, Pages 572-582

  Cervantes, Jair ^a   Li, Xiaoou ^a   Yu, Wen ^a  

^a DEPARTAMENTO DE FÍSICA   (Mexico)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL METHODS; CONVERGENCE OF NUMERICAL METHODS; DATA STRUCTURES; FUZZY CONTROL; PROBLEM SOLVING; VECTORS;

COMPUTATIONAL COSTS; DATA SETS; FUZZY CLUSTERING; SUPPORT VECTOR MACHINES;

CLASSIFICATION (OF INFORMATION);

EID: 33845934479     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11925231_54     Document Type: Conference Paper

References (20)

1. Awad M., Khan L., Bastani F. y Yen I. L., "An Effective support vector machine (SVMs) Performance Using Hierarchical Clustering," Proceedings of the 16th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'04) - Volume 00, 2004 November 15-17, 2004 Pages: 663-667
2. st IEEE Int. Conf. on Data Mining., IEEE Computer Society 2001, pp. 43-50.
3. Chih-Chung Ch., and Chih-Jen L., LIBSVM: a library for support vector machines, 2001, http://www.csie.ntu.edu.tw/~cjlin/libsvm.
4. Collobert R. y Bengio S., " SVMTorch: support vector machine for large regresion problems". Journal of Machine Learning Research, 1:143-160, 2001.
5. Daniael B. y Cao D.,"Training support vector machine Using Adaptive Clustering", in Proc. of SIAM Int. Conf on Data Mining 2004, Lake Buena Vista, FL, USA
6. Joachims T.,"Making large-scale support vector machine learning practical". In A.S.B. Scholkopf, C. Surges, editor, Advances in Kernel Methods: support vector machine. MIT Press, Cambridge, MA 1998.
7. S.W.Kim; Oommen, B.J.; Enhancing prototype reduction schemes with recursion: a method applicable for "large" data sets, IEEE Transactions on Systems, Man and Cybernetics, Part B, Volume 34, Issue 3, 1384-1397, 2004
8. Lebrun, G.; Charrier, C.; Cardot, H.; SVM training time reduction using vector quantization, Proceedings of the 17th International Conference on pattern recognition, Volume 1, 160-163,2004.
9. K.Li; H.K.Huang; Incremental learning proximal support vector machine classifiers, Proceedings, 2002 International Conference on machine learning and cybernetics, Volume 3, 1635-1637, 2002
10. Luo F., Khan L., Bastani F., Yen I., y Zhou J., "A Dynamical Growing Self Organizing Tree (DGSOT) for Hierarquical Clustering Gene Expression Profiles", Bioinformatics, Volume 20, Issue 16, 2605-2617, 2004.
11. Pavlov, D.; Mao, J.; Dom, B.; Scaling-up support vector machine using boosting algorithm, Proceedings of 15th International Conference on pattern recognition, Volume 2, 219-222, 2000
12. Platt J., "Fast Training of support vector machine using sequential minimal optimization. In A.S.B. Scholkopf, C. Burges, editor, Advances in Kernel Methods: support vector machine. MIT Press, Cambridge, MA 1998.
13. Rui Xu; Wunsch, D., II., "Survey of clustering algorithms", IEEE Transactions on Neural Networks, Volume 16, Issue 3, May 2005 Page(s): 645-678
14. Schohn G. y Cohn D., "Less is more : Active Learning with support vector machine", In Proc. 17th Int. Conf. Machine Learning, Stanford, CA, 2000.
15. Shih L., Rennie D.M., Chang Y. y Karger D.R., "Text Bundling: Statistics-based Data Reduction", In Proc of the Twentieth Int. Conf. on Machine Learning (ICML-2003), Washington DC, 2003.
16. Tong S. y Koller D., "Support vector machine active learning with applications to text clasifications", In Proc. 17th Int. Conf. Machine Learning, Stanford, CA, 2000
17. Vapnik V., "The Nature of Statistical Learning Theory," Springer, N.Y., 1995.
18. Van Gestel, T.; Suykens, J.A.K.; De Moor, B.; Vandewalle, J.; Bayesian inference for LS-SVMs on large data sets using the Nystrom method, Proceedings of the 2002 International Joint Conference on neural networks, Volume 3, 2779-2784, 2002
19. th ACM SIGKDD 2003, August 24-27, 2003, Washington, DC, USA.
20. R.Xu, D.Wunsch, Survey of Clustering Algorithms, IEEE Trans. Neural Networks, vol. 16, pp.645-678, 2005.