Better multiclass classification via a margin-optimized single binary problem

Pattern Recognition Letters

Volumn 29, Issue 14, 2008, Pages 1954-1959

  El Yaniv, Ran ^a   Pechyony, Dmitry ^a   Yom Tov, Elad ^b  

^a TECHNION ISRAEL INSTITUTE OF TECHNOLOGY   (Israel)

^b IBM HAIFA RESEARCH LAB   (Israel)

Author keywords

Multiclass classification; Multiple kernel learning; Support vector machines

Indexed keywords

CLASSIFIERS; LEARNING SYSTEMS; PROGRAMMING THEORY;

BINARY PROBLEMS; CODING SCHEMES; EMPIRICAL EXAMINATION; GENERALIZATION ERRORS; LARGE MARGINS; LINEAR COMBINATIONS; MULTI-CLASS CLASSIFIERS; MULTI-CLASS PROBLEMS; MULTICLASS CLASSIFICATION; MULTIPLE KERNEL LEARNING; SUPPORT VECTOR MACHINES;

CLASSIFICATION (OF INFORMATION);

EID: 50149098403     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2008.06.012     Document Type: Article

References (26)

1. Allwein E.L., Schapire R.E., and Singer Y. Reducing multiclass to binary: A unifying approach for margin classifiers. JMLR 1 (2000) 113-141
2. Anguita, D., Ridella, S., Sterpi, D., 2004. A new method for multiclass support vector machines. In: Proceedings on the International Joint Conference on Neural Networks, pp. 407-412.
3. Bordes A., Ertekin S., Weston J., and Bottou L. Fast kernel classifiers with online and active learning. JMLR 6 (2005) 1579-1619
4. Bousquet, O., Herrmann, D., 2003. On the complexity of learning the kernel matrix. In: NIPS.
5. Canu S., and Smola A. Kernel methods and the exponential family. Neurocomputing 69 (2006) 714-720
6. Collobert R., and Bengio S. SVMTorch: Support vector machines for large-scale regression problems. JMLR 1 (2001) 143-160
7. Demšar J. Statistical comparisons of classifiers over multiple data sets. JMLR 7 (2006) 1-30
8. Dietterich T.G., and Bakiri G. Solving multiclass learning problems via error-correcting output codes. JAIR 2 (1995) 263-286
9. Duda R.O., and Hart P.E. Pattern Classification and Scene Analysis (1973), Wiley, New York
10. Eves H. Elementary Matrix Theory (1980), Dover Publications
11. Friedman, J.H., 1996. Another approach to polychotomous classification. Technical Report, Stanford University.
12. Har-Peled, S., Roth, D., Zimak, D., 2003. Constraint classification for multiclass classification and ranking. In: NIPS.
13. Hsu C.W., and Lin C.J. A comparison of methods for multi-class support vector machines. IEEE Trans. Neural Networks 13 (2002) 415-425
14. Keerthi S., Chapelle O., and DeCoste D. Building support vector machines with reduced classifier complexity. JMLR 6 (2006) 1493-1515
15. Lanckriet G., Cristianini N., Bartlett P., El-Ghaoui L., and Jordan M. Learning the kernel matrix via semidefinite programming. JMLR 5 (2004) 27-72
16. Lee Y., Lin Y., and Wahba G. Multicategory support vector machines, theory, and application to the classification of microarray data and satellite radiance data. J. Amer. Statist. Assoc. 99 (2004) 67-81
17. McAllester D. Generalization bounds and consistency for structured labeling. In: BakIr G., et al. (Ed). Predicting Structured Data (2007), MIT Press
18. Rifkin, R., 2002. Everything old is new again: A fresh look at historical approaches in machine learning. PhD Thesis, MIT.
19. Rifkin R., and Klautau A. In defense of one-vs.-all classification. JMLR 5 (2004) 101-141
20. Sejnowski T.G., and Rosenberg C.R. Parallel networks that learn to pronounce English text. J. Complex Syst. 1 1 (1987) 145-168
21. Srebro, N., Ben-David, S., 2006. Learning bounds for support vector machines with learned kernels. In: COLT, pp. 169-183.
22. Tsang I., Kwok J., and Cheung P. Core vector machines: Fast svm training on very large data sets. JMLR 5 (2005) 363-392
23. Tsochantaridis I., Joachims T., Hofmann T., and Altun Y. Large margin methods for structured and interdependent output variables. JMLR 6 (2005) 1453-1484
24. Vapnik V. Statistical Learning Theory (1998), Wiley Interscience
25. Zhang T. Statistical analysis of some multi-category large margin classification methods. JMLR (2004)
26. Zien, A., Ong, C.S., 2007. Multiclass multiple kernel learning. In: ICML.