A new cross-training approach by using labeled data

Authors:
Dongshan Huang;Enmin Song;Guangzhi Ma;Huirong Zhan;Chih-Cheng Hung
Affiliations:
Huazhong University of Science and Technology, Wuhan, China;Huazhong University of Science and Technology, Wuhan, China;Huazhong University of Science and Technology, Wuhan, China;Huazhong University of Science and Technology, Wuhan, China;Southern Polytechnic State University, Marietta, GA
Venue:
Proceedings of the 2009 ACM symposium on Applied Computing
Year:
2009

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Abstract

We propose a new cross-training based learning algorithm in this paper. This algorithm generates three classifiers based on the three subsets of original labeled and unlabeled training set. The proposed algorithm is evaluated using data from the UCI repository by the experiment. Experimental results show that our algorithm can improve classification accuracy compared to those of other algorithms.