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There is a growing body of literature about ensemble techniques for imbalance learning in recent years, the various extensions of imbalanced classification methods were established from different points of view. The present study is initiated in an attempt to review the state-of-the-art ensemble classification algorithms for dealing with imbalanced datasets, offering a comprehensive analysis for incorporating the dynamic selection of base classifiers in classification. By conducting 14 existing ensemble algorithms incorporating a dynamic selection on 56 datasets, the experimental results reveal that the classical algorithm with a dynamic selection strategy deliver a practical way to improve the classification performance for both a binary class and multi-class imbalanced datasets. In addition, by combining patch learning with a dynamic selection ensemble classification, a patch-ensemble classification method is designed, which utilizes the misclassified samples to train patch classifiers for increasing the diversity of base classifiers. The experiments\u2019 results indicate that the designed method has a certain potential for the performance of multi-class imbalanced classification.<\/jats:p>","DOI":"10.3390\/e23070822","type":"journal-article","created":{"date-parts":[[2021,6,28]],"date-time":"2021-06-28T11:45:40Z","timestamp":1624880740000},"page":"822","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Experimental Study and Comparison of Imbalance Ensemble Classifiers with Dynamic Selection Strategy"],"prefix":"10.3390","volume":"23","author":[{"given":"Dongxue","family":"Zhao","sequence":"first","affiliation":[{"name":"School of Science, Dalian Maritime University, Dalian 116026, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Science, Dalian Maritime University, Dalian 116026, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yashuang","family":"Mu","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence and Big Data, Henan University of Technology, Zhengzhou 450001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1462-9443","authenticated-orcid":false,"given":"Lidong","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Science, Dalian Maritime University, Dalian 116026, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,6,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Fasihi, M., Nadimi-Shahraki, M.H., and Jannesari, A. 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