Feature selection for multi-label learning based on variable-degree multi-granulation decision-theoretic rough sets

DOI10.1016/J.IJAR.2024.109181zbMATH Open1543.68381MaRDI QIDQ6570325

Jin Qian, Duoqian Miao, Pengfei Zhao, Ming Wan, Ying Yu, Zhi-Qiang Zhang

Publication date: 10 July 2024

Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)

zbMATH Keywords

uncertaintyrough setsfeature selectionmulti-label learningthree-way decision

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Reasoning under uncertainty in the context of artificial intelligence (68T37) Computational aspects of data analysis and big data (68T09)

Cites Work

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• Multiple Comparisons Among Means
• A Comparison of Alternative Tests of Significance for the Problem of $m$ Rankings
• A novel multi-label feature selection method with association rules and rough set

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