Model selection for SVM using imitative scale chaos optimization algorithm

Journal of Shanghai University

Volumn 10, Issue 6, 2006, Pages 531-534

  Liu, Qing Kun ^a   Que, Pei Wen ^a   Fei, Chun Guo ^a   Song, Shou Peng ^a  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

Author keywords

imitative scale chaos optimization (MSCO); model selection; non destructive testing (NDT); support vector machine (SVM); ultrasonic testing (UT)

Indexed keywords

EID: 84867920836     PISSN: 10076417     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11741-006-0052-3     Document Type: Article

References (7)

1. Cristianini N, Shawe-Taylor J. An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods[M]. Cambridge University Press, England, 2000.
2. Hsu C W, Chang C C, Lin C J. A practical guide to support vector classification. 2003.
3. Cristianini N, Campbell C, Shawe-Taylor J. Dynamically Adapting Kernels in Support Vector Machines[R]. Technical Report, NC2-TR-1998-017, NeuroCOLT2, 1998.
4. K M Chung W C Kao C L Sun, et al. 2003 Radius margin bounds for support vector machines with the rbf kernel[J] Neural Computation 7 1 70 78
5. S S Keerthi C J Lin 2003 Asymptotic behaviors of support vector machines with Gaussian kernel[J] Neural Computation 15 3 1667 1689 1086.68569 10.1162/089976603321891855
6. Tong Zhang Hong-wei Wang Zi-cai Wang 1999 Mutative scale chaos optimization algorithm and its application [J] Control and Decision 14 3 285 288 1057.62531 (in Chinese)
7. Wickerhauser M V. Adaptive Wavelet Analysis from Theory to Software[M]. Welleysley, MA, 1994.