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Polyhedral Separability Through Successive LP
Authors:Astorino  A.  Gaudioso  M.
Affiliation:(1) Istituto per la Sistemistica e l'Informatica, ISI CNR, Rende, Cosenza, Italia;(2) Dipartimento di Elettronica, Informatica e Sistemistica, Università della Calabria, Rende, Cosenza, Italia
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
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