A Semi-Supervised Regression Algorithm Based on Co-Training with SVR - KNN
Yu Qing Li, Meng Tian · Advanced materials research · 2014
A semi-supervised regression algorithm based on co-training with the same type KNN required large amount of storage capacity and shown scarcely to improve the regression precision further after several iterations. This paper puts forward a kind of a semi-supervised regression algorithm based on co-training with SVR-KNN, which fully combined the advantages of SVR and KNN in a semi-supervised learning respectively, avoided the learning ability limitations of a single type of learning. Finally, comparative experiments of the semi-supervised regression algorithm based on co-training with SVR-KNN and the other two co-training algorithms with same type learners was conducted, the result shows that the algorithm proposed here works much better in improving regression precision and generalizing the regression model.