Abstract
This paper proposes a novel hypersphere support vector machines based on multiplicative updates. This algorithm can obtain the boundary of hypersphere containing one class of samples by the description of the training samples from one class and uses this boundary to classify the test samples. Moreover, new multiplicative updates are derived to solve sum and box constrained quadratic programming. The experiments show the superiority of our new algorithm.
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References
Sha, F., Saul, L.K., Lee, D.D.: Multiplicative updates for nonnegative quadratic programming in support vector machines. In: Neural and Information processing systems, vol. 15, MIT press, Cambridge (2003)
Vapnik, V.: Nature of satistical learning theory. Springer, New York (2000)
Lu, C.D., Zhang, T.Y., Hu, J.Y.: Support vector Domain Classifier Based on Multiplicative Updates. Chinese Journal of Computers 27, 690–694 (2004)
Gentile, C.: A new approximate maximal margin classification algorithm. Journal of Machine Learning Research 2, 213–242 (2001)
Tax, D., Ypma, A., Duin, R.: Support vector domain description. Pattern Recognition letters 20, 1191–1199 (1999)
Platt, J.C.: Sequential minimal optimization: A fast algorithm for training support vector machines. In: Advance in kernel methods: Support vector machines, MIT Press, Cambridge (1998)
Joachims, T.: Making Large-scale Support Vector Machine Learning Practical. In: Advance in kernel methods: Support vector machines, pp. 169–184. MIT Press, Cambridge (1999)
Blake, C.L., Merz, C.J.: UCI Repository of Machine Learning Databases. University of California, Irvine (1998), http://www.ics.vci.edu/mlearn/MLRepostory.html
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© 2006 Springer-Verlag Berlin Heidelberg
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Wu, Q., Liu, S., Zhang, L. (2006). Hypersphere Support Vector Machines Based on Multiplicative Updates. In: Jiao, L., Wang, L., Gao, Xb., Liu, J., Wu, F. (eds) Advances in Natural Computation. ICNC 2006. Lecture Notes in Computer Science, vol 4221. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881070_1
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DOI: https://doi.org/10.1007/11881070_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45901-9
Online ISBN: 978-3-540-45902-6
eBook Packages: Computer ScienceComputer Science (R0)