Polyhedral Separability Through Successive LP

A. Astorino and M. Gaudioso
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A. Astorino: Istituto per la Sistemistica e l'Informatica, ISI CNR
M. Gaudioso: Università della Calabria

Journal of Optimization Theory and Applications, 2002, vol. 112, issue 2, No 2, 265-293

Abstract: Abstract We address the problem of discriminating between two finite point sets $$\mathcal{A}{\text{ and }}\mathcal{B}$$ in the n-dimensional space by h hyperplanes generating a convex polyhedron. If the intersection of the convex hull of $$\mathcal{A}{\text{ with }}\mathcal{B}$$ is empty, the two sets can be strictly separated (polyhedral separability). We introduce an error function which is piecewise linear, but not convex nor concave, and define a descent procedure based on the iterative solution of the LP descent direction finding subproblems.

Keywords: Classification; separability; machine learning (search for similar items in EconPapers)
Date: 2002
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Citations: View citations in EconPapers (8)

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DOI: 10.1023/A:1013649822153

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