A Strategy of Maximizing the Sum of Weighted Margins for Ranking Multi Classification Problem

Author

Luo, Linkai ; Lin, Chengde ; Peng, Hong ; Zhou, Qifeng

fYear

2006

fDate

5-8 Dec. 2006

Firstpage

1

Lastpage

5

Abstract

This paper discusses the strategies of maximizing the sum of margins for ranking multi classification problem. First, the strategy of maximizing the sum of margins (MSM) is extended to maximizing the sum of weighted margins (MSWM). Using MSWM, a mathematical model is established to deal with the ranking multi classification problems where the importance of margins between classes is different, and its dual model is deduced. Then, by introducing the concept of algebraic margin, which is a generalization of geometric margin, the MSWM is further extended to maximizing the sum of weighed algebraic margins (MSWAM). Based on the MSWAM, the deduced mathematical model of the ranking multi classification problem not only has positive generalization ability, but is also a simple linear programming model

Keywords

algebra; linear programming; pattern classification; support vector machines; algebraic margin; generalization; geometric margin; linear programming; mathematical model; ranking multiclassification problem; weighted margin sum maximization; Automation; Control systems; Linear programming; Mathematical model; Size control; Support vector machine classification; Support vector machines; SVM; algebraic margin; ranking multi classification; sum of weighted margin;

fLanguage

English

Publisher

ieee

Conference_Titel

Control, Automation, Robotics and Vision, 2006. ICARCV '06. 9th International Conference on

Conference_Location

Singapore

Print_ISBN

1-4244-0341-3

Electronic_ISBN

1-4214-042-1

Type

conf

DOI

10.1109/ICARCV.2006.345287

Filename

4150309