DocumentCode
2095110
Title
A Modified Self-Training Semi-supervised SVM Algorithm
Author
Jin, Yun ; Ma, Yong ; Zhao, Li
Author_Institution
Sch. of Phys. & Electron. Eng., Xuzhou Normal Univ., Xuzhou, China
fYear
2012
fDate
11-13 May 2012
Firstpage
224
Lastpage
228
Abstract
In this paper, we present a modified self-training semi-supervised SVM algorithm. In order to demonstrate its validity and effectiveness, we carry out some experiments which prove that our method is better than the former algorithm. Using our modified self-training semi-supervised SVM algorithm, we can save much time for labeling the unlabelled data.
Keywords
data handling; learning (artificial intelligence); pattern classification; support vector machines; SVM algorithm; modified self-training semi-supervised learning; support vector machine; unlabelled data; Classification algorithms; Convergence; Data models; Iris recognition; Optimization; Support vector machines; Training; SVM; UCI; self-training; semi-supervised learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Communication Systems and Network Technologies (CSNT), 2012 International Conference on
Conference_Location
Rajkot
Print_ISBN
978-1-4673-1538-8
Type
conf
DOI
10.1109/CSNT.2012.56
Filename
6200629
Link To Document