Feature selection for microarray data using least squares SVM and particle swarm optimization

Proceedings of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB '05

Volumn 2005, Issue , 2005, Pages

  Tang, E K ^a   Suganthan, P N ^a   Yao, X ^b  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^b UNIVERSITY OF BIRMINGHAM   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BIOMEDICAL ENGINEERING; DATA REDUCTION; DNA; LEARNING SYSTEMS; LEAST SQUARES APPROXIMATIONS; PROBLEM SOLVING;

FEATURE SELECTIONS; LEAST SQUARES SUPPORT VECTOR MACHINE (LSSVM); PARTICLE SWARM OPTIMIZATION (PSO);

FEATURE EXTRACTION;

EID: 33847192815     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/cibcb.2005.1594892     Document Type: Conference Paper

References (12)

1. T. Golub, D. Slonim, P. Tamayo, C. Huard, M. Gaasenbeek, J. Mesirov, H. Coller, M. Loh, J. Downing, M. Caligiuri, C. Bloomfield, and E. Lander, "Molecular classification of cancer: class discovery and class prediction by gene expression monitoring," Science, vol. 286, pp.531-537, 1999.
2. P. Devijver and J. Kittler, Pattern recognition: a statistical approach. Prentice Hall, London, 1982.
3. I. Guyon, J. Weston, S. Barnhill and V. Vapnik, "Gene selection for cancer classification using support vector machines," Machine Learning, vol. 46, pp. 389-422, 2002.
4. M. L. Raymer, W. F. Punch, E. D. Goodman, L. A. Kuhn and A. K. Jain, "Dimensionality Reduction Using Genetic Algorithms," IEEE Trans. Evolutionary Computation, vol. 4, pp. 164-171, 2000.
5. A. Rakotomamonjy, "Variable selection using SVM-based criteria," Journal of Machine Learning Research, vol. 3, pp. 1357-1370, 2003.
6. X. Zhou and K. Z. Mao, "LS Bound based gene selection for DNA microarray data," Bioinformatics, vol. 21, 1559-1564, 2005.
7. J. A. K. Suykens, T. Van Gestel, J. De Brabanter, B. De Moor, and J. Vandewalle, Least Squares Support Vector Machines. World Scientific, Singapore, 2002.
8. O. Chapelle, V. Vapnik, O. Bousquet, and S. Mukherjee, "Choosing multiple parameters for support vector machines," Machine Learning, vol. 46, pp. 131-159, 2002.
9. J. Platt, "Probabilities for support vector machines," Advances in large margin classifiers, A. Smola, P. Bartlett, B. Schölkopf, and D. Schuurmans, Eds. MIT Press, Cambridge, MA, 2000.
10. Available: http://www.esat.kuleuven.ac.be/~npochet/Bioinformatics/
11. R. C. Eberhart and J. Kennedy, "A new optimizer using particle swarm theory," Proc. Sixth International Symposium on Micro Machine and Human Sciende (Nagoya, Japan), pp. 39-43, 1995.
12. T. Hastie, R. Tibshirani, and J. Friedman, The elements of statistical learning: data mining, inference, and prediction. Springer, 2001.