Sparse low-redundancy multi-label feature selection with adaptive dynamic dual graph constraints

Yanhong Wu; Jianxia Bai

doi:10.1007/s10489-024-06205-3

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Sparse low-redundancy multi-label feature selection with adaptive dynamic dual graph constraints

Yanhong Wu Jianxia Bai

Year: 2024 Journal: Applied Intelligence Vol: 55 (3) Publisher: Springer Science+Business Media

DOI: 10.1007/s10489-024-06205-3

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Keywords:

Computer science Redundancy (engineering) Feature selection Graph Minimum redundancy feature selection Artificial intelligence Pattern recognition (psychology) Machine learning Data mining Theoretical computer science

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Text and Document Classification Technologies

Physical Sciences → Computer Science → Artificial Intelligence

Advanced Image and Video Retrieval Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Face and Expression Recognition

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Sparse low-redundancy multi-label feature selection with adaptive dynamic dual graph constraints

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