A Global Optimization Approach to Classification

作     者：Bagirov, Adil M. Rubinov, Alexander M. Yearwood, John 

作者机构：Univ Ballarat Sch Informat Technol & Math Sci Ballarat Vic 3353 Australia 

出 版 物：《OPTIMIZATION AND ENGINEERING》 (最优化与工程学)

年 卷 期：2002年第3卷第2期

页      面：129-155页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 0701[理学-数学] 

主　　题：classification feature selection cutting angle method convex programming 

摘      要：We reduce the classification problem to solving a global optimization problem and a method based on a combination of the cutting angle method and a local search is applied to the solution of this problem. The proposed method allows to solve classification problems for databases with an arbitrary number of classes. Numerical experiments have been carried out with databases of small to medium size. We present their results and provide comparisons of these results with those obtained by 29 different classification algorithms. The best performance overall was achieved with the global optimization method.