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Solving Discriminant Models Using Interior Point Algorithm

  • Conference paper
Data Mining and Knowledge Management (CASDMKM 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3327))

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Abstract

In this paper we first survey the linear programming based discriminant models in the literature. We then propose an interior point algorithm to solve the linear programming. The algorithm is polynomial with simple starting point.

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Author information

Authors and Affiliations

  1. Institute of Policy and Management, Chinese Academy of Sciences, Beijing, 100080, China

    Siming Huang, Guoliang Yang & Chao Su

Authors
  1. Siming Huang
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  2. Guoliang Yang
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  3. Chao Su
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Editor information

Editors and Affiliations

  1. Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing 100080, China; College of Information Science and Technology, University of Nebraska at Omaha, 68182, Omaha, NE, USA

    Yong Shi

  2. Institute of Policy & Management, Chinese Academy of Sciences, P.O. Box, 100080, Beijing, P.R. China

    Weixuan Xu

  3. College of Information Science and Technology, University of Nebraska at Omaha, 68182, NE, USA

    Zhengxin Chen

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© 2004 Springer-Verlag Berlin Heidelberg

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Huang, S., Yang, G., Su, C. (2004). Solving Discriminant Models Using Interior Point Algorithm. In: Shi, Y., Xu, W., Chen, Z. (eds) Data Mining and Knowledge Management. CASDMKM 2004. Lecture Notes in Computer Science(), vol 3327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30537-8_6

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  • DOI: https://doi.org/10.1007/978-3-540-30537-8_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23987-1

  • Online ISBN: 978-3-540-30537-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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