SVM model selection with the VC bound

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

Volumn 3314, Issue , 2004, Pages 1067-1071

  Li, Huaqing ^a   Wang, Shaoyu ^a   Qi, Feihu ^a  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

BENCHMARKING;

BENCHMARK DATASETS; COARSE-TO-FINE SEARCHES; COMPARATIVE PERFORMANCE; HYBRID ALGORITHMS; MODEL SELECTION; PERFORMANCE; PREDEFINED RANGE; SEARCH STRATEGIES; SUPPORT VECTOR MACHINE MODELS; SUPPORT VECTORS MACHINE; CROSS VALIDATION ALGORITHMS; SVM MODEL;

SUPPORT VECTOR MACHINES;

EID: 35048818013     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-30497-5_164     Document Type: Article

References (6)

1. Burges, C.J.: A Tutorial on Support Vector Machines for Pattern Recognition. Data Mining and Knowledge Discovery. 2 (1998) 121-267
2. Chung, K.-M., Kao, W.-C., Sun, T., Wang, L.-L., Lin, C.-J.: Radius Margin Bounds for Support Vector Machines with the RBF Kernel. Neural Computation. 11 (2003) 2643-2681
3. Chang, C.-C., Lin, C.-J.: LIBSVM: A Library for Support Vector Machines. (2002) Online at http://www.csie.ntu.edu.tw/~cjlin/papers/libsvm.pdf
4. Staelin, C.: Parameter Selection for Support Vector Machines. (2003) Online at http://www.hpl.hp.com/techreports/2002/HPL-2002-354R1.pdf
5. Li, H.-Q., Wang, S.-Y., Qi, F.-H: Minimal Enclosing Sphere Estimation and Its Application to SVMs Model Selection. IEEE Intl. Symposium on Neural Networks. (2004) to appear
6. Chapelle, O., Vapnik, V., Bousquet, O., Mukherjee, S: Choosing Multiple Parameters for Support Vector Machines. Machine Learning. 46 (2002) 131-159