Selection of Pattern Features by Mathematical Programming Algorithms

The selection of a "best" subset of features from a given set is considered for the case where a multiplicity of constraints are present in the two-class pattern recognition problem. The problem can be formulated with a Lagrangian multiplier and an efficient iterative technique used in conjunction with dynamic programming procedures to obtain a solution when two constraints are present. The problem can be formulated in integer programming terms and use made of available integer programming computer algorithms for solution when multiple constraints are present. The Lemke-Spielberg zero-one integer algorithm is particularly useful, but other integer programming algorithms can be used also.