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The labels are supported by intra-cluster positive samples, determined using fuzzy rough set theory, which helps to capture the consensus label set. Experimental results on multi-label datasets using four classifiers demonstrate the effectiveness of the proposed method in terms of macro-F1 and micro-F1 scores.<\/jats:p>","DOI":"10.1007\/s40747-024-01498-w","type":"journal-article","created":{"date-parts":[[2024,6,6]],"date-time":"2024-06-06T08:02:38Z","timestamp":1717660958000},"page":"6267-6282","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["An oversampling algorithm of multi-label data based on cluster-specific samples and fuzzy rough set theory"],"prefix":"10.1007","volume":"10","author":[{"given":"Jinming","family":"Liu","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0416-4515","authenticated-orcid":false,"given":"Kai","family":"Huang","sequence":"additional","affiliation":[]},{"given":"Chen","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Jian","family":"Mao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,6,6]]},"reference":[{"key":"1498_CR1","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1007\/s00500-008-0323-y","volume":"13","author":"J Alcal\u00e1-Fdez","year":"2009","unstructured":"Alcal\u00e1-Fdez J, Sanchez L, Garcia S et al (2009) Keel: a software tool to assess evolutionary algorithms for data mining problems. 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