Help-training for semi-supervised discriminative classifiers. Application to SVM

In this paper, we propose to reinforce self-training strategy by using a generative classifier that may help the main discriminative classifier training in semi-supervised mode to label the unlabeled data. We called this semi-supervised strategy: help-training. We apply this method for training support vector machine with labeled and unlabeled data. Experimental results on both artificial and real problems show its usefulness comparing with other classical semi-supervised methods.