RESEARCH ON MULTI-VIEW SEMI-SUPERVISED LEARNING ALGORITHM BASED ON CO-LEARNING

摘要：

Recent years multi-view semi-supervised learning has become research focus. In most cases multiple views are often supposed to be given previous to learning. However it is not the case in the real-world application, which makes multi-view semi-supervised learning algorithms impractical and infeasible. A view partitioning method called ViewPartition was proposed. Its used to partition input features into two parts. Based on ViewPartition, a new multi-view semisupervised learning algorithm called Co-VP was presented.Co-VP can construct classifiers from labeled and unlabeled data. Studies comparing classification algorithms have found Co-VP to be comparable in performance with classification trees and with neural network classifiers. They have also exhibited high accuracy when applied to real-world databases, especially for those with more redundant features.

关键词： Semi-supervised learning multiple views view partitioning back propagation

作者: XING-QI WANG

作者单位: School of Computer Science, Hangzhou Dianzi University, Hangzhou 310018 P.R.China;CERCIA, School of Computer Science, the University of Birmingham, Edgbaston, Birmingham, United Kingdom

会议类型: 国际会议

会议名称: 2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

会议地点: 大连

会议语种:英文

页码: 1276-1280

在线出版日期: 2006-08-13（万方平台首次上网日期，不代表论文的发表时间）