摘要：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.
