摘要 : We study the two-group classification problem which involves classifying an observation into one of two groups on its attributes. The classification rule is a hyperplane which misclassifies the fewest number of observations in the... 展开 We study the two-group classification problem which involves classifying an observation into one of two groups on its attributes. The classification rule is a hyperplane which misclassifies the fewest number of observations in the training sample. Exact and heuristic algorithms for solving the problem are presented. Computational results confirm the efficiency of this approach. 收起