DocumentCode
2194397
Title
A KKT Condition Based DDAGSVM Classifier
Author
Sun, Wei ; Shi, Zhao-Hui ; Bai, Dong-Ying
Author_Institution
Missile Inst., Air Force Eng. Univ., Sanyuan, China
fYear
2009
fDate
17-19 Oct. 2009
Firstpage
1
Lastpage
4
Abstract
Decision directed acyclic graph support vector machine (DDAGSVM) has been proposed to extend SVM from binary classification problems to multi-class classifications. But the generalization ability is subject to the structure of DDAG. To improve the classification accuracy, a novel separability measure is defined based on Karush-Kuhn-Tucher (KKT) condition, and an improved DDAGSVM has been given. The experimental results show that this algorithm has higher generalization ability.
Keywords
decision trees; radar; support vector machines; DDAGSVM classifier; ESM radar; Karush-Kuhn-Tucher condition; binary classification; binary classification problems; decision directed acyclic graph support vector machine; multiclass classifications; radar information; Kernel; Lagrangian functions; Missiles; Polynomials; Sun; Support vector machine classification; Support vector machines; Training data;
fLanguage
English
Publisher
ieee
Conference_Titel
Biomedical Engineering and Informatics, 2009. BMEI '09. 2nd International Conference on
Conference_Location
Tianjin
Print_ISBN
978-1-4244-4132-7
Electronic_ISBN
978-1-4244-4134-1
Type
conf
DOI
10.1109/BMEI.2009.5305527
Filename
5305527
Link To Document