{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T16:18:11Z","timestamp":1790007491676,"version":"4.0.1"},"reference-count":14,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2021,5,27]],"date-time":"2021-05-27T00:00:00Z","timestamp":1622073600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61772152"],"award-info":[{"award-number":["61772152"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Basic Research Project","award":["JCKY2019604C004"],"award-info":[{"award-number":["JCKY2019604C004"]}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2019YFB1406300"],"award-info":[{"award-number":["2019YFB1406300"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Youth Fund Project of Humanities and Social Sciences Research of the Ministry of Education of China","award":["20YJCZH172"],"award-info":[{"award-number":["20YJCZH172"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>As the classic feature selection algorithm, the Relief algorithm has the advantages of simple computation and high efficiency, but the algorithm itself is limited to only dealing with binary classification problems, and the comprehensive distinguishing ability of the feature subsets composed of the former K features selected by the Relief algorithm is often redundant, as the algorithm cannot select the ideal feature subset. When calculating the correlation and redundancy between characteristics by mutual information, the computation speed is slow because of the high computational complexity and the method\u2019s need to calculate the probability density function of the corresponding features. Aiming to solve the above problems, we first improve the weight of the Relief algorithm, so that it can be used to evaluate a set of candidate feature sets. Then we use the improved joint mutual information evaluation function to replace the basic mutual information computation and solve the problem of computation speed and correlation, and redundancy between features. Finally, a compound correlation feature selection algorithm based on Relief and joint mutual information is proposed using the evaluation function and the heuristic sequential forward search strategy. This algorithm can effectively select feature subsets with small redundancy and strong classification characteristics, and has the excellent characteristics of faster calculation speed.<\/jats:p>","DOI":"10.3390\/info12060228","type":"journal-article","created":{"date-parts":[[2021,5,27]],"date-time":"2021-05-27T11:07:02Z","timestamp":1622113622000},"page":"228","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Improved Relief Weight Feature Selection Algorithm Based on Relief and Mutual Information"],"prefix":"10.3390","volume":"12","author":[{"given":"Hongbin","family":"Wang","sequence":"first","affiliation":[{"name":"College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pengming","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shengchun","family":"Deng","sequence":"additional","affiliation":[{"name":"School of Information Management and Artificial Intelligence, Zhejiang University of Finance and Economics, Hangzhou 310018, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haoran","family":"Li","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,5,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/S0004-3702(97)00043-X","article-title":"Wrappers for feature subset selection","volume":"97","author":"Kohavi","year":"1997","journal-title":"Artif. 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Proceedings of the International Conference on Inventive Systems and Control (ICISC), Coimbatore, India.","DOI":"10.1109\/ICISC.2017.8068746"}],"container-title":["Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2078-2489\/12\/6\/228\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:08:49Z","timestamp":1760162929000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2078-2489\/12\/6\/228"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,27]]},"references-count":14,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2021,6]]}},"alternative-id":["info12060228"],"URL":"https:\/\/doi.org\/10.3390\/info12060228","relation":{},"ISSN":["2078-2489"],"issn-type":[{"value":"2078-2489","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,5,27]]}}}