A p-norm Discrimination Model for Two Linearly Inseparable Sets

Pavlo Krokhmal (), Robert Murphey (), Panos M. Pardalos () and Zhaohan Yu ()
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Pavlo Krokhmal: University of Iowa
Robert Murphey: Air Force Research Lab
Panos M. Pardalos: University of Florida
Zhaohan Yu: University of Iowa

Chapter Chapter 18 in Dynamics of Information Systems, 2010, pp 335-352 from Springer

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.

Keywords: Linear Programming Problem; Discrimination Model; Separation Model; Conic Constraint; Steiner Minimum Tree (search for similar items in EconPapers)
Date: 2010
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Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-1-4419-5689-7_18

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DOI: 10.1007/978-1-4419-5689-7_18

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