Support vector machines with evolutionary feature weights optimization for biomedical data classification

Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS

Volumn 2005, Issue , 2005, Pages 177-180

  Jin, Bo ^a   Zhang, Yan Qing ^a  

^a GEORGIA STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA PROCESSING; DATA REDUCTION; DATABASE SYSTEMS; LEARNING SYSTEMS; OPTIMIZATION; PROBLEM SOLVING;

DATA MODIFICATION; RAW DATA; REAL WORLD APPLICATIONS; SUPPORT VECTOR MACHINES (SVM);

BIOMEDICAL ENGINEERING;

EID: 33745003246     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (15)

1. Vapnik, V., The Nature of Statistical Learning Theory, New York, Springer, 1995.
2. Cortes, C. And Vapnik, V., "Support-vector networks," Machine Learning, vol. 20, pp. 273-297, 1995.
3. Vapnik, V., Statistical Learning Theory, New York, John Wiley and Sons, 1998.
4. Noble, William Stafford, "Support Vector Machine Applications in Computational Biology," Kernel Methods in Computational Biology, B. Schoelkopf, K. Tsuda and J.-P. Vert, ed., MIT Press, 2004.
5. Huang, Han-Pang and Liu, Yi-Hung "Fuzzy Support Vector Machines for Pattern Recognition and Data Mining," International Journal of Fuzzy Systems, Vol. 4, No.3, 2002.
6. Liu, Chun-Fu and Sheng-De Wang, "Fuzzy support vector machines," IEEE Transactions on Neural Networks, Vol. 13, No. 2, pp. 464-471, 2002.
7. Inoue, T And Abe, S., "Fuzzy support vector machines for pattern classification," Proceedings of the International Joint Conference on Neural Networks (IJCNN'01), pp. 1449-1454, 2000.
8. H. Fröhlich, O. Chapelle, B. Schölkopf, "Feature Selection for Support Vector Machines using Genetic Algorithms," 15th IEEE International Conference on Tools with Artificial Intelligence, pp. 142-148, 2003.
9. Chiang, Jung-Hsien and Hao, Pei-Yi, "A New Kernel-Based Fuzzy Clustering Approach: Support Vector Clustering With Cell Growing," IEEE Transactions on Fuzzy Systems, Vol. 11, No. 4, pp. 518-527, 2003
10. H. Yu, J. Yang and J. Han, "Classifying large data sets using SVMs with hierarchical clusters," Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining, ACM Press, Washington, D.C., 2003.
11. Y.C. Tang, B. Jin, Y. Sun, Y.-Q. Zhang, "Granular Support Vector Machines for Medical Binary Classification Problems," Proc. of IEEE CIBIB 2004, San Diego, Oct. 7-8, 2004.
12. Z. Michalewicz, "Genetic Algorithms + Data Structures = Evolution Programs," Springer Verlag, Berlin, 1996.
13. Blake, C.L. & Merz, C.J. (1998). UCI Repository of machine learning databases, Irvine, CA: University of California, Department of Information and Computer Science. Available: http://www.ics.uci.edu/~mlearn/MLRepository.html
14. O. L. Mangasarian and W. H. Wolberg: "Cancer diagnosis via linear programming," SIAM News, vol. 23, no. 5, pp. 1-18, Sep. 1990.
15. T. Joachims, "Making Large-Scale SVM Learning Practical. Advances in Kernel Methods - Support Vector Learning," MIT Press, 1999.