TITLE

A Semi-Supervised Learning Algorithm Based on Modified Self-training SVM

AUTHOR(S)
Yun Jin; Chengwei Huang; Li Zhao
PUB. DATE
July 2011
SOURCE
Journal of Computers;Jul2011, Vol. 6 Issue 7, p1438
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
In this paper, we first introduce some facts about semi-supervised learning and its often used methods such as generative mixture models, self-training, co-training and Transductive SVM and so on. Then we present a self-training semi-supervised SVM algorithm based on which we give out a modified 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 and obtain a better classifier with good performance.
ACCESSION #
64144038

 

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