A review of research on co‐training
Xin Ning, Xinran Wang, Shaohui Xu, Weiwei Cai, Liping Zhang, Lina Yu, Wenfa Li
Abstract
Summary Co‐training algorithm is one of the main methods of semi‐supervised learning in machine learning, which explores the effective information in unlabeled data by multi‐learner collaboration. Based on the development of co‐training algorithm, the research work in recent years was further summarized in this article. In particular, three main steps of relevant co‐training algorithms are introduced: view acquisition, learners' differentiation, and label confidence estimation. Finally, we summarized the problems existing in the current co‐training methods, gave some suggestions for improvement, and looked forward to the future development direction of the co‐training algorithm.