Abstract
On the basis of research on the mechanism of the support vector machine (SVM) and the distribution characteristics of support vectors, a class center-based algorithm of pre-extracting support vectors was proposed. First, a hyperplane band was constructed via the class centers of two classes of samples and the width of the band was reduced via iteration; then, the samples within the band were employed in training as an alternative to the entire training samples, thus reducing the training samples and meanwhile excluding some outliers; and finally, the algorithm proposed was tested via artificial data and UCI data, and the results of the simulation experiments indicate that when the influence on the classification precision is modest, the proposed algorithm can significantly increase the training speed.
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References
Vapnik, V.N.: The Nature of Statistical Learning Theory. Springer (1995)
Osuna, E., Freund, R.: An Improved Training Algorithm for Support Vector Machines. In: Proceedings of the IEEE Workshop on Neural Networks for Signal Processing, pp. 276–285 (1997)
Platt, J.C.: Sequential Minimal Optimization: A fast algorithm for training support vector machines, pp. 169–182. The MIT Press, Cambridge (1998)
Cao, L.J., Keerthi, S.S., et al.: Parallel Sequential Minimal Optimization for the Training of Support Vector Machines. IEEE Transaction on Neural Networks 17(4), 1039–1049 (2006)
Li, H.-L., Wang, C.-H., Yuan, B.-Z.: An Improved SVM: NN-SVM. Chinese Journal of Computers 26(8), 1015–1020 (2003)
Ye, F., Luo, J.-Q., Yu, Z.-F.: An Improvement SVM Learning Algorithm with Parallel Processing. Microelectronics & Computer 26(2), 40–43 (2009)
Zheng, C.H., Jiao, L.C.: Fuzzy Pre-extracting Method for Support Vector Machine. In: Proceedings of the 1st International Conference on Machine Learning and Cybernetics, pp. 2026–2030 (2002)
Jiao, L.-C., Zhang, L., Zhou, W.-D.: Pre-extracting Support Vectors for Support Vector Machine. Acta Electronic Sinic 29(3), 383–386 (2001)
Li, Q., Jiao, L.-C., Zhou, W.-D.: Pre-extracting Support Vector for Support Vector Machine Based on Vector Projection. Chinese Journal of Computers 28(2), 145–152 (2005)
Wu, Q., Liu, S.-Y., Du, Z.: Fuzzy Support Vector Machine Method Based on Border Vector Extraction. Pattern Recognition and Artificial Intelligence 21(3), 332–337 (2008)
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Shiwei, Y., Yunxing, S. (2012). Center-Based Iteration Algorithm of Pre-extracting Support Vectors. In: Liu, C., Wang, L., Yang, A. (eds) Information Computing and Applications. ICICA 2012. Communications in Computer and Information Science, vol 307. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34038-3_106
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DOI: https://doi.org/10.1007/978-3-642-34038-3_106
Publisher Name: Springer, Berlin, Heidelberg
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