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This paper introduces the idea of parallel ensemble learning and proposes a new hybrid Bayesian network structure learning algorithm. The algorithm adopts the elite-based structure learner using genetic algorithm (ESL-GA) as the base learner. Firstly, the adjacency matrices of the network structures learned by ESL-GA are weighted and averaged. Then, according to the preset threshold, the edges between variables with weak dependence are filtered to obtain a fusion matrix. Finally, the fusion matrix is modified as the adjacency matrix of the integrated Bayesian network so as to obtain the final Bayesian network structure. Comparative experiments on the standard Bayesian network data sets show that the accuracy and reliability of the proposed algorithm are significantly better than other algorithms.<\/jats:p>","DOI":"10.3233\/ida-226818","type":"journal-article","created":{"date-parts":[[2023,6,9]],"date-time":"2023-06-09T10:14:55Z","timestamp":1686305695000},"page":"1103-1120","source":"Crossref","is-referenced-by-count":8,"title":["An improved hybrid structure learning strategy for Bayesian networks based on ensemble learning"],"prefix":"10.1177","volume":"27","author":[{"given":"Wenlong","family":"Gao","sequence":"first","affiliation":[{"name":"Institute of Epidemiology and Health Statistics, School of Public Health, Lanzhou University, Lanzhou, Gansu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhimei","family":"Zeng","sequence":"additional","affiliation":[{"name":"School of Mathematics and Statistics, Lanzhou University, Lanzhou, Gansu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaojie","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Mathematics and Statistics, Lanzhou University, Lanzhou, Gansu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongsong","family":"Ke","sequence":"additional","affiliation":[{"name":"School of Mathematics and Statistics, Lanzhou University, Lanzhou, Gansu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Minqian","family":"Zhi","sequence":"additional","affiliation":[{"name":"School of Mathematics and Statistics, Lanzhou University, Lanzhou, Gansu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","reference":[{"issue":"3","key":"10.3233\/IDA-226818_ref1","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1016\/0004-3702(86)90072-X","article-title":"Fusion, propagation, and structuring in belief networks","volume":"29","author":"Pearl","year":"1986","journal-title":"Artificial Intelligence"},{"key":"10.3233\/IDA-226818_ref2","doi-asserted-by":"crossref","unstructured":"J. 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