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Support Vector Classification with Nominal Attributes

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Computational Intelligence and Security (CIS 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3801))

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Abstract

This paper presents a new algorithm to deal with nominal attributes in Support Vector Classification by modifying the most popular approach. For a nominal attribute with M states, we translate it into M points in M – 1 dimensional space with flexible and adjustable position. Their final position is decided by minimizing the Leave-one-out error. This strategy overcomes the shortcoming in the most popular approach which assume that any two different attribute values have the same degree of dissimilarities. Preliminary experiments also show the superiority of our new algorithm.

This work is supported by the National Natural Science Foundation of China (No.10371131).

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References

  1. Schölkopf, B., Smola, A.J.: Learning with Kernels-Support Vector Machines, Regularization, Optimization, and Beyond. The MIT Press, Cambridge (2002)

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Author information

Authors and Affiliations

  1. Chinese Academy of Sciences Research Center on Data Technology & Knowledge Economy, Beijing, 100080, China

    Yingjie Tian

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

    Naiyang Deng

Authors
  1. Yingjie Tian
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  2. Naiyang Deng
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Editor information

Editors and Affiliations

  1. Microelectronic Instiute, Xidian University, 710071, Xi’an, China

    Yue Hao

  2. Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong

    Jiming Liu

  3. School of Computer Science and Technology, Xidian University, Xi’an, China

    Yuping Wang

  4. Department of Computer Science, Hong Kong Baptist University, Hong Kong,  

    Yiu-ming Cheung

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

  6. Life Science Research Center, School of Electronic Engineering, Xidian University, 710071, Xi’an, Shaanxi, China

    Licheng Jiao

  7. Key Laboratory of Computer Networks and Information Security (Ministry of Education), Xidian University, 710071, Xi’an, China

    Jianfeng Ma

  8. National Laboratory of Antennas and Microwave Technology, Xidian University, 710071, Xi’an, Shanxi, P.R. China

    Yong-Chang Jiao

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© 2005 Springer-Verlag Berlin Heidelberg

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Tian, Y., Deng, N. (2005). Support Vector Classification with Nominal Attributes. In: Hao, Y., et al. Computational Intelligence and Security. CIS 2005. Lecture Notes in Computer Science(), vol 3801. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596448_86

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  • DOI: https://doi.org/10.1007/11596448_86

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30818-8

  • Online ISBN: 978-3-540-31599-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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