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A novel SVM multi-class classifier based on pairwise coupling

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3 Author(s)
Zeyu Li ; Center for Inf. Sci., Peking Univ., Beijing, China ; Shiwei Tang ; Jing Xue

In this paper, a novel algorithm is proposed to tackle multi-class classification problems. For a K-class classification task, an array of K optimal pairwise coupling classifiers (O-PWC) is constructed, each of which is optimal to the corresponding class and provides a reliable probability estimation for that class. The classification accuracy rate is improved while the computational cost does not increase too much. At the same time, a more accurate estimation of posterior probabilities for a given pattern can be acquired. This algorithm is applied to face recognition on an ORL face database. Experimental results reveal that our method is effective and efficient.

Published in:

Systems, Man and Cybernetics, 2002 IEEE International Conference on  (Volume:7 )

Date of Conference:

6-9 Oct. 2002

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