Feature Selection via Mathematical Programming

December 23, 2014

The problem of discriminating between two fi nite point sets in n-dimensional feature space by a separating plane that utilizes as few of the features as possible, is formulated as a mathematical program with a parametric objective function and linear constraints. The step function that appears in the objective function can be approximated by a sigmoid or by a concave exponential on the nonnegative real line, or it can be treated exactly by considering the equivalent linear
program with equilibrium constraints (LPEC).

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