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A p-norm Discrimination Model for Two Linearly Inseparable Sets

In: Dynamics of Information Systems

Author

Listed:
  • Pavlo Krokhmal

    (University of Iowa)

  • Robert Murphey

    (Air Force Research Lab)

  • Panos M. Pardalos

    (University of Florida)

  • Zhaohan Yu

    (University of Iowa)

Abstract

Summary We propose a new p-norm linear discrimination model that generalizes the model of Bennett and Mangasarian (Optim. Methods Softw. 1:23–34, 1992) and reduces to linear programming problems with p-order conic constraints. We demonstrate that the developed model possesses excellent methodological and computational properties (e.g., it does not allow for a null separating hyperplane when the sets are linearly separable, etc.). The presented approach for handling linear programming problems with p-order conic constraints relies on construction of polyhedral approximations for p-order cones. A case study on several popular data sets that illustrates the advantages of the developed model is conducted.

Suggested Citation

  • Pavlo Krokhmal & Robert Murphey & Panos M. Pardalos & Zhaohan Yu, 2010. "A p-norm Discrimination Model for Two Linearly Inseparable Sets," Springer Optimization and Its Applications, in: Michael J. Hirsch & Panos M. Pardalos & Robert Murphey (ed.), Dynamics of Information Systems, chapter 0, pages 335-352, Springer.
    • Handle: RePEc:spr:spochp:978-1-4419-5689-7_18
    DOI: 10.1007/978-1-4419-5689-7_18
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