Fuzzy Support Vector Classification Based on Fuzzy Chance Constrained Programming

Author

Yang, Zhimin ; Liu, GuangLi

Author_Institution

Coll. of Zhijiang, Zhejiang Univ. of Technol., Hangzhou

Volume

1

fYear

2006

fDate

Nov. 2006

Firstpage

180

Lastpage

182

Abstract

This paper is concerned with the fuzzy support vector classification in which the type of both the output of the training point and the value of the final fuzzy classification function is triangle fuzzy number. First, the fuzzy classification problem is formulated as a fuzzy chance constrained programming. Then we transform this programming into its equivalence quadratic programming. As a result, we propose fuzzy support vector classification algorithm. In order to show its rationality of the algorithm, an example is presented

Keywords

constraint handling; fuzzy set theory; learning (artificial intelligence); pattern classification; quadratic programming; support vector machines; fuzzy chance constrained programming; fuzzy support vector classification; machine learning; quadratic programming; triangle fuzzy number; Classification algorithms; Educational institutions; Functional programming; Fuzzy sets; Linear programming; Machine learning; Machine learning algorithms; Quadratic programming; Support vector machine classification; Support vector machines; Machine learning; fuzzy support vector classification; possibility measure; triangle fuzzy number;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Security, 2006 International Conference on

Conference_Location

Guangzhou

Print_ISBN

1-4244-0605-6

Electronic_ISBN

1-4244-0605-6

Type

conf

DOI

10.1109/ICCIAS.2006.294117

Filename

4072070