An experimental comparison of some recently developed linear programming approaches to the discriminant problem

This article studies and evaluates several recently proposed linear programming formulations to solve classification problems in discriminant analysis. Some of the new linear programming formulations have merits and perform well in a simulation experiment. A weighted deviation approach is introduced to correct the imbalance of misclassifications across the two groups.