Help-training semi-supervised LS-SVM
Mathias M. Adankon, Mohamed Cheriet · 2009
Help-training for semi-supervised learning was proposed in our previous work in order to reinforce self-training strategy by using a generative classifier along with the main discriminative classifier. This paper extends the Help-training method to least squares support vector machine (LS-SVM) where labeled and unlabeled data are used for training. Experimental results on both artificial and real problems show its usefulness when comparing with other classical semisupervised methods.