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Despite their efficiency, LCSs are not capable of handling imperfect information, which may lead to reduced performance in terms of classification accuracy. We propose a new accuracy-based Michigan-style LCS that integrates the belief function theory in the supervised classifier system. The belief function or evidence theory represents an efficient framework for treating imperfect information. The new approach shows promising results in real world classification problems. <\/jats:p>","DOI":"10.1142\/s0219622022500997","type":"journal-article","created":{"date-parts":[[2022,11,16]],"date-time":"2022-11-16T15:46:21Z","timestamp":1668613581000},"page":"917-938","source":"Crossref","is-referenced-by-count":2,"title":["Evidential Supervised Classifier System: A New Learning Classifier System Dealing with Imperfect Information"],"prefix":"10.1142","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7954-585X","authenticated-orcid":false,"given":"Rahma","family":"Ferjani","sequence":"first","affiliation":[{"name":"SMART Lab, Institut Sup\u00e9rieur de Gestion de Tunis (ISG Tunis), Universit\u00e9 de Tunis, Rue de la libert\u00e9, Bardo 2000, Tunisia"}]},{"given":"Lilia","family":"Rejeb","sequence":"additional","affiliation":[{"name":"SMART Lab, Institut Sup\u00e9rieur de Gestion de Tunis (ISG Tunis), Universit\u00e9 de Tunis, Rue de la libert\u00e9, Bardo 2000, Tunisia"}]},{"given":"Chedi","family":"Abdelkarim","sequence":"additional","affiliation":[{"name":"SMART Lab, Institut Sup\u00e9rieur de Gestion de Tunis (ISG Tunis), Universit\u00e9 de Tunis, Rue de la libert\u00e9, Bardo 2000, Tunisia"}]},{"given":"Lamjed Ben","family":"Said","sequence":"additional","affiliation":[{"name":"SMART Lab, Institut Sup\u00e9rieur de Gestion de Tunis (ISG Tunis), Universit\u00e9 de Tunis, Rue de la libert\u00e9, Bardo 2000, Tunisia"}]}],"member":"219","published-online":{"date-parts":[[2022,12,28]]},"reference":[{"volume-title":"Data Mining: Concepts and Techniques","year":"2011","author":"Han J.","key":"S0219622022500997BIB001"},{"doi-asserted-by":"publisher","key":"S0219622022500997BIB002","DOI":"10.1109\/TSMC.2021.3049604"},{"doi-asserted-by":"publisher","key":"S0219622022500997BIB003","DOI":"10.1016\/j.dss.2020.113429"},{"key":"S0219622022500997BIB004","first-page":"81","volume-title":"Machine Learning","volume":"1","author":"Quinlan J. 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