A p-norm discrimination model for two linearly inseparable sets

Pavlo Krokhmal, Robert Murphey, Panos M. Pardalos, Zhaohan Yu

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish (US)
Pages (from-to)335-352
Number of pages18
JournalSpringer Optimization and Its Applications
Volume40
DOIs
StatePublished - Jan 1 2010
Externally publishedYes

ASJC Scopus subject areas

  • Control and Optimization

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