A Semi-Supervised Regression Algorithm Based on Co-Training with SVR - KNN

Abstract:

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.

• Periodical: Advanced Materials Research (Volumes 926-930)
• Pages: 2914-2918
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.926-930.2914
• Online since: May 2014
• Authors: Yu Qing Li*, Meng Tian
• Keywords: Co-Training, KNN, Regression Algorithm, Semi-Supervised Learning, SVR

References

[1] CHAPELLE O, SCHOLKOPF B and ZIEN A. Semi-supervised Learning. Cambridge: MIT Press, (2006).

DOI: 10.7551/mitpress/9780262033589.001.0001

[2] ZHOU Zhihua, WANG Jue. Machine learning and its application. BEIJING: Tsinghua university press, 2007: 259-275.

[3] A. Blum, T. Mitchell. Combining labeled and unlabeled data with co-training. In: Proceedings of the 11th Annual Conference on Computational Learning Theory (COLT'98), Wisconsin, MI, 1998, 92-100.

DOI: 10.1145/279943.279962

[4] Zhou Z.H., Li M. Semi-supervised regression with co-training style algorithm. IEEE Transactions on Knowledge and Data Engineering, 2007, 19(11): 1479一1493.

[5] Glenn Fung, O.L. Mangasarian. Semi-supervised Support Vector Machines for Unlabeled Data Classification, Optimization Methods and Software, 2001, 15: 29~44.

DOI: 10.1080/10556780108805809

[6] BIAN Zhaoqi, ZHANG Xuegong. Pattern Recognition. BEIJING: Tsinghua university press, (2000).

[7] ZHU X J. Semi-supervised Learning Literature Survey. Madison: University of Wisconsin , (2008).

[8] Pang-Ning Tan, Michael Steinbach, Vipin Kumar. Introduction to Data Mining. People Post Press, (2006).