Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6897800 | European Journal of Operational Research | 2013 | 6 Pages |
Abstract
We consider a p-norm linear discrimination model that generalizes the model of Bennett and Mangasarian (1992) and reduces to a linear programming problem with p-order cone constraints. The proposed approach for handling linear programming problems with p-order cone constraints is based on reformulation of p-order cone optimization problems as second order cone programming (SOCP) problems when p is rational. Since such reformulations typically lead to SOCP problems with large numbers of second order cones, an “economical” representation that minimizes the number of second order cones is proposed. A case study illustrating the developed model on several popular data sets is conducted.
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Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Yana Morenko, Alexander Vinel, Zhaohan Yu, Pavlo Krokhmal,