Half-against-half multi-class support vector machines

Lecture Notes in Computer Science

Volumn 3541, Issue , 2005, Pages 156-164

  Lei, Hansheng ^a   Govindaraju, Venu ^a  

^a the State University of New York   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL METHODS; ESTIMATION; MATHEMATICAL MODELS;

HALF-AGAINST-HALF (HAH); ONE-AGAINST-ALL (OVA) METHODS; ONE-AGAINST-ONE (OVO) METHODS; SVM CLASSIFIER;

VECTORS;

EID: 26444579317     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/11494683_16     Document Type: Conference Paper

References (14)

1. Boser, B., I.Guyon, Vapnik, V.: A training algorithm for optimal margin classifiers. In Haussler, D., ed.: 5th Annual ACM Workshop on COLT. (1992) 144-152
2. Bredensteiner, E., Bennet, K.: Multicategory classification by support vector machines. In: Computational Optimizations and Applications. Volume 12. (1999) 53-79
3. Crammer, K., Singer, Y.: On the algorithmic implementation of multiclass kernel-based vector machines. Journal of Machine Learning Research vol. 2 (2001) 265-292
4. Vapnik, V.: Statistical Learning Theory. Wiley, New York (1998)
5. Kreßel, U.: Pairwise classification and support vector machines. In: Advances in Kernel Methods: Support Vector Learnings, Cambridge, MA, MIT Press (1999) 255-268
6. Platt, J., Cristianini, N., Shawe-Taylor, J.: Large margin DAGs for multiclass classification. In: Advances in Neural Information Processing Systems. Volume 12. (2000) 547-553
7. Hsu, C., Lin, C.: A comparison of methods for multi-class support vector machines. IEEE Transactions on Neural Networks 13 (2002) 415-425
8. Rifin, R., Klautau, A.: In defense of one vs-all-classification. Journal of Machine Learning Research vol. 5 (2004) 101-141
9. Hettich, S., Bay, S.: The UCI KDD archive. (1999)
10. Liu, X., Xing, H., Wang, X.: A multistage support vector machine. In: The 2nd International Conference on Machine Learning and Cybernetics. (2003) 1305-1308
11. Ben-Hur, A., Horn, D., Siegelmann, H., Vapnik, V.: Support vector clustering. Journal of Machine Learning Research vol. 2 (2001) 125-137
12. Platt, J.: Fast training of support vector machines using sequential minimal optimization. In: Advances in Kernel Methods - Support Vector Learning, Cambridge, MA, MIT Press (1999) 185-208
13. C.Chang, Lin, C.: Libsvm: a library for support vector machines. (2001)
14. Schölkopf, B., Smola, A., Williamson, R., Bartlett, P.: New support vector algorithms. Neural Computation 12 (2000) 1207C1245