Fuzzy support vector classification based on fuzzy chance constrained programming

被引：0
|
作者：
Yang, Zhimin [1 ]
Liu, Guangli [2 ]
机构：
[1] Zhengzhou Univ Technol, Coll Zhijiang, Hangzhou 310024, Peoples R China
[2] China Agr Univ, Coll Informat & Elect Engn, Beijing 100083, Peoples R China
来源：
2006 INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND SECURITY, PTS 1 AND 2, PROCEEDINGS | 2006年
基金：
中国国家自然科学基金;
关键词：
machine learning; fuzzy support vector classification; possibility measure; triangle fuzzy number;
D O I：
10.1109/ICCIAS.2006.294117
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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, a example is presented.
引用
收藏
页码：180 / 182
页数：3
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