Author(s): Ning, X (Ning, Xin); Wang, XR (Wang, Xinran); Xu, SH (Xu, Shaohui); Cai, WW (Cai, Weiwei); Zhang, LP (Zhang, Liping); Yu, LA (Yu, Lina); Li, WF (Li, Wenfa)

Source: CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE Article Number: e6276 DOI: 10.1002/cpe.6276 Early Access Date: MAR 2021

Abstract: 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.

Accession Number: WOS:000630700400001

Author Identifiers:

Author        Web of Science ResearcherID        ORCID Number

Cai, Weiwei         AAH-5456-2020         0000-0001-6795-6152

ISSN: 1532-0626

eISSN: 1532-0634

Full Text: https://onlinelibrary.wiley.com/doi/10.1002/cpe.6276