Abstract
The Optimal Pairwise Coupling (O-PWC) classifier was proposed and used for data classification because of its excellent classification performance [1]. A key step in the O-PWC algorithm is to calculate a number of posterior probabilities, which was achieved using an iterative procedure in [1],[2]. In this paper, we will present an analytical solution to the problem of finding the posterior probabilities. As a result, the computational efficiency of the O-PWC algorithm will be significantly improved, which will be shown by one numerical example.
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Li, Z., Tang, S.: Face Recognition Using Improved Pairwise Coupling Support Vector Machines. In: Proceedings of the 9th International Conference on Neural Information Processing (2002)
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Hastie, T., Tibshirani, R.: Classification by Pairwise Coupling. In: NIPS 1997 (1996)
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© 2005 Springer-Verlag Berlin Heidelberg
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Xu, R., Qian, T., Kwan, C. (2005). An Improved Optimal Pairwise Coupling Classifier. In: Wang, J., Liao, XF., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3497. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427445_6
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DOI: https://doi.org/10.1007/11427445_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25913-8
Online ISBN: 978-3-540-32067-8
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