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An Improved Optimal Pairwise Coupling Classifier

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Advances in Neural Networks – ISNN 2005 (ISNN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3497))

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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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References

  1. 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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  2. Platt, J.: Probabilistic Outputs for SVMs and Comparisons to Regularized Likehood Methods, Advances in Large Margin Classifiers. MIT Press, Cambridge (1999)

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  3. 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

  • eBook Packages: Computer ScienceComputer Science (R0)

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