Fully Bayesian analysis of the relevance vector machine classification for imbalanced data problem-Reference-Cited by-同舟云学术

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Fully Bayesian analysis of the relevance vector machine classification for imbalanced data problem

Published:2022-06-17 Issue:1 Volume:8 Page:192-205
ISSN:2468-2322
Container-title:CAAI Transactions on Intelligence Technology
language:en
Short-container-title:CAAI Trans on Intel Tech

Author:

Wang Wenyang¹²^ORCID,Sun Yanna¹,Li Keran²,Wang Jinglin³,He Chong⁴,Sun Dongchu⁵⁶

Affiliation:

1. School of Maritime Economics and Management Dalian Maritime University Dalian China

2. Collaborative Innovation Center for Transport Studies Dalian Maritime University Dalian China

3. Maritime Safety and Environmental Management World Maritime University Malmö Sweden

4. Department of Statistics University of Nebraska‐Lincoln Lincoln Nebraska USA

5. School of Statistics Faculty of Economics and Management East China Normal University Shanghai China

6. Department of Statistics University of Missouri Columbia Missouri USA

Publisher

Institution of Engineering and Technology (IET)

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Vision and Pattern Recognition,Human-Computer Interaction,Information Systems

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/cit2.12111

Reference36 articles.

1. Support-vector networks

2. Sparse bayesian learning and the relevance vector machine;Tipping M.E;J. Mach. Learn. Res,2001

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