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A Hybrid Bayesian Network Structure Learning Algorithm in Equivalence Class Space

  • Northwestern Polytechnical University Xian

科研成果: 书/报告/会议事项章节会议稿件同行评审

2 引用 (Scopus)

摘要

Greedy equivalence search (GES) is a well-known Bayesian network structure learning algorithm in equivalence class space (E-space). However, the extensive search space limits the efficiency of GES. In this paper, we propose a hybrid method to improve GES. We use mutual information to determine the strongly connected components (SCCs) graph. The SCCs graph is converted to E-space, and we take it as the initial graph of GES. The experiments reveal that our proposed approach significantly prunes the search space of GES and improves the efficiency of GES. Compared with the state-of-The-Art methods, our method also has excellent accuracy.

源语言英语
主期刊名2023 8th International Conference on Control and Robotics Engineering, ICCRE 2023
出版商Institute of Electrical and Electronics Engineers Inc.
1-4
页数4
ISBN(电子版)9798350345650
DOI
出版状态已出版 - 2023
活动8th International Conference on Control and Robotics Engineering, ICCRE 2023 - Niigata, 日本
期限: 21 4月 202323 4月 2023

丛书

姓名2023 8th International Conference on Control and Robotics Engineering, ICCRE 2023

会议

会议8th International Conference on Control and Robotics Engineering, ICCRE 2023
国家/地区日本
Niigata
时期21/04/2323/04/23

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