Multi-label classification using a fuzzy rough neighborhood consensus

DOI10.1016/j.ins.2017.12.034zbMath1436.68313OpenAlexW2778359823MaRDI QIDQ781943

Sarah Vluymans, Yvan Saeys, Francisco Herrera, Chris Cornelis

Publication date: 20 July 2020

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2017.12.034

zbMATH Keywords

multi-label classificationnearest neighbor classificationfuzzy rough set theory

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Reasoning under uncertainty in the context of artificial intelligence (68T37)

Related Items (8)

Attribute reduction for multi-label classification based on labels of positive region ⋮ A dynamic approach for updating the lower approximation in adjustable multi-granulation rough sets ⋮ Fuzzy extensions of the dominance-based rough set approach ⋮ Label correlation in multi-label classification using local attribute reductions with fuzzy rough sets ⋮ Improving multi-label classification with missing labels by learning label-specific features ⋮ A three-way selective ensemble model for multi-label classification ⋮ Weight selection strategies for ordered weighted average based fuzzy rough sets ⋮ Applications of rough sets in big data analysis: an overview

Uses Software

• ML-KNN
• MultiP-SChlo

Cites Work

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• ROUGH FUZZY SETS AND FUZZY ROUGH SETS*
• NON-NULL RANKING MODELS. I
• On ordered weighted averaging aggregation operators in multicriteria decisionmaking
• Rough sets
• Multi-Label Dictionary Learning for Image Annotation
• Fuzzy sets
• Nearest neighbor pattern classification

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