Abstract
Support Vector Machine is a statistical learning machine developed by Vapnik in his statistical learning theory. This machine present very interesting proprieties in both classification and regression problems in the high dimensional space. In this paper, we propose β_SVM, a new kernel function for SVM, with special proprieties and high discrimination ability. We have applied this kernel in the pattern recognition, and we have compare the different performances of many other kernels, results show that the new kernel is very performant.
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© 2003 Springer-Verlag Wien
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Hamdani, T.M., Alimi, A.M. (2003). β_SVM a new Support Vector Machine kernel. In: Pearson, D.W., Steele, N.C., Albrecht, R.F. (eds) Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-0646-4_13
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DOI: https://doi.org/10.1007/978-3-7091-0646-4_13
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-00743-3
Online ISBN: 978-3-7091-0646-4
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