Multigroup discriminant analysis using linear programming
成果类型：
Article
署名作者：
Gochet, W; Stam, A; Srinivasan, V; Chen, SX
署名单位：
University System of Georgia; University of Georgia; Stanford University; Nanyang Technological University; International Institute for Applied Systems Analysis (IIASA)
刊物名称：
OPERATIONS RESEARCH
ISSN/ISSBN：
0030-364X
DOI：
10.1287/opre.45.2.213
发表日期：
1997
页码：
213-225
关键词：
摘要：
In this paper we introduce a nonparametric linear programming formulation for the general multigroup classification problem. Previous research using linear programming formulations has either been limited to the two-group case, or required complicated constraints and many zero-one variables. We develop general properties of our multigroup formulation and illustrate its use with several small example problems and previously published real data sets. A comparative analysis on the real data sets shows that our formulation may offer an interesting robust alternative to parametric statistical formulations for the multigroup discriminant problem.