Article ID Journal Published Year Pages File Type
1136045 Computers & Industrial Engineering 2006 16 Pages PDF
Abstract
The aim of this article is to consider a new linear programming and two goal programming models for two-group classification problems. When these approaches are applied to the data of real life or of simulation, our proposed new models perform well both in separating the groups and the group-membership predictions of new objects. In discriminant analysis some linear programming models determine the attribute weights and the cut-off value in two steps, but our models determine simultaneously all of these values in one step. Moreover, the results of simulation experiments show that our proposed models outperform significantly than existing linear programming and statistical approaches in attaining higher average hit-ratios.
Related Topics
Physical Sciences and Engineering Engineering Industrial and Manufacturing Engineering
Authors
, , ,