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Support Vector Regression with Smoothing Property

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Advances in Natural Computation (ICNC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3610))

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Abstract

The problem of construction of smoothing curve is actually regression problem. How to use SVR to solve the problem of curve smoothing reconstruction in reverse engineering is discussed in this paper. A modified support vector regression model is proposed. Numerical result shows that the smoothness of curves fitted by modified method is better than by the standard SVR, when there are some bad measure points in the data.

Supported by the National Natural Science foundation of China (No.10371131).

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References

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Author information

Authors and Affiliations

  1. College of Science, China Agricultural University, 100083, Beijing, China

    Zhixia Yang, Nong Wang & Ling Jing

Authors
  1. Zhixia Yang
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  2. Nong Wang
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  3. Ling Jing
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Editor information

Editors and Affiliations

  1. School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, 639798, Singapore

    Lipo Wang

  2. School of Software, Sun Yat-Sen University, 510275, Guangzhou, China

    Ke Chen

  3. School of Computer Engineering, Nanyang Technological University, BLK N4, 2b-39, Nanyang Avenue, 639798, Singapore

    Yew Soon Ong

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© 2005 Springer-Verlag Berlin Heidelberg

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Yang, Z., Wang, N., Jing, L. (2005). Support Vector Regression with Smoothing Property. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3610. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539087_25

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  • DOI: https://doi.org/10.1007/11539087_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28323-2

  • Online ISBN: 978-3-540-31853-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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