{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:20:25Z","timestamp":1760149225036,"version":"build-2065373602"},"reference-count":21,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2023,7,19]],"date-time":"2023-07-19T00:00:00Z","timestamp":1689724800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"UGR-FEDER funds","award":["A-TIC-344-UGR20","P20_00159"],"award-info":[{"award-number":["A-TIC-344-UGR20","P20_00159"]}]},{"name":"FEDER\/Junta de Andaluc\u00eda-Consejer\u00eda de Transformaci\u00f3n Econ\u00f3mica, Industria, Conocimiento y Universidades","award":["A-TIC-344-UGR20","P20_00159"],"award-info":[{"award-number":["A-TIC-344-UGR20","P20_00159"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Imprecise classification is a relatively new task within Machine Learning. The difference with standard classification is that not only is one state of the variable under study determined, a set of states that do not have enough information against them and cannot be ruled out is determined as well. For imprecise classification, a mode called an Imprecise Credal Decision Tree (ICDT) that uses imprecise probabilities and maximum of entropy as the information measure has been presented. A difficult and interesting task is to show how to combine this type of imprecise classifiers. A procedure based on the minimum level of dominance has been presented; though it represents a very strong method of combining, it has the drawback of an important risk of possible erroneous prediction. In this research, we use the second-best theory to argue that the aforementioned type of combination can be improved through a new procedure built by relaxing the constraints. The new procedure is compared with the original one in an experimental study on a large set of datasets, and shows improvement.<\/jats:p>","DOI":"10.3390\/e25071088","type":"journal-article","created":{"date-parts":[[2023,7,19]],"date-time":"2023-07-19T21:20:14Z","timestamp":1689801614000},"page":"1088","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Upgrading the Fusion of Imprecise Classifiers"],"prefix":"10.3390","volume":"25","author":[{"given":"Seraf\u00edn","family":"Moral-Garc\u00eda","sequence":"first","affiliation":[{"name":"Department of Computer Science and Artificial Intelligence, University of Granada, 18012 Granada, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mar\u00eda D.","family":"Ben\u00edtez","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Artificial Intelligence, University of Granada, 18012 Granada, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9018-5165","authenticated-orcid":false,"given":"Joaqu\u00edn","family":"Abell\u00e1n","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Artificial Intelligence, University of Granada, 18012 Granada, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,7,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1215","DOI":"10.1002\/int.10143","article-title":"Building classification trees using the total uncertainty criterion","volume":"18","author":"Moral","year":"2003","journal-title":"Int. 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