An improved SVM classifier

ICIC Express Letters

Volumn 3, Issue 4, 2009, Pages 1001-1005

  Gao, Hong ^a   Liu, Wei ^a  

^a DALIAN MARITIME UNIVERSITY   (China)

Author keywords

Classification; Nearest neighbor; Support vector machine

Indexed keywords

CLASSIFICATION; DECISION SURFACES; GENERALIZATION ABILITY; NEAREST NEIGHBORS; SVM CLASSIFIERS; TRAINING ERRORS; TRAINING SETS;

VECTORS;

SUPPORT VECTOR MACHINES;

EID: 77953906729     PISSN: 1881803X     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (8)

1. V. N. Vapnik, Statistical Learning Theory, 2nd ed., NY: Springer-Verlag,NewYork, 2003.
2. N. Begum, M. A. Fattah and F. J. Ren, Automatic text summarization usingsupport vector machine, International Journal of Innovative Computing,Information and Control, vol.5, no.7, pp.1987-1996, 2009.
3. K. C. Lam, E. Palaneeswaran, and C. Y. Yu, A support vector machine modelfor contractor prequalification, Automation in Construction, vol.18, no.3,pp.321-329, 2009.
4. Q. S. She, H. Y. Su, L. D. Dong and J. Chu, Support vector machine withadaptive parameters in image coding, International Journal of InnovativeComputing, Information and Control, vol.4, no.2, pp.359-367, 2008.
5. H. Y. Wu, C. Y. Hsu, T. F. Lee and F. M. Fang, Improved SVM and ANN inincipient fault diagnosis of power transformers using clonal selectionalgorithms, International Journal of Innovative Computing, Information andControl, vol.5, no.7, pp.1959-1974, 2009.
6. H. X. Ke, and X. G. Zhang, Editing support vector machine, Proc. of theIEEE International Joint Conference on Neural Networks, Piscataway,pp.1464- 1467, 2001.
7. Z. C. Yu and H. T. Yu, A method of nearest neighbor queries for movingobjects, International Journal of Innovative Computing, Information and Control,vol.4, no.4, pp.927-932, 2008.
8. N. Japkowicz and S. Stephen, The class imbalance problem: A systematicstudy, Intelligent Data Analysis, vol.6, no.5, pp.429-450, 2002.