Semi-supervised feature selection by minimum neighborhood redundancy and maximum neighborhood relevancy

Damo Qian; Keyu Liu; Shiming Zhang; Xibei Yang

doi:10.1007/s10489-024-05578-9

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Semi-supervised feature selection by minimum neighborhood redundancy and maximum neighborhood relevancy

Damo Qian Keyu Liu Shiming Zhang Xibei Yang

Year: 2024 Journal: Applied Intelligence Vol: 54 (17-18)Pages: 7750-7764 Publisher: Springer Science+Business Media

DOI: 10.1007/s10489-024-05578-9

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Keywords:

Computer science Redundancy (engineering) Feature selection Selection (genetic algorithm) Pattern recognition (psychology) Artificial intelligence Minimum redundancy feature selection Data mining

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Image Retrieval and Classification Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Face and Expression Recognition

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Rough Sets and Fuzzy Logic

Physical Sciences → Computer Science → Computational Theory and Mathematics

Semi-supervised feature selection by minimum neighborhood redundancy and maximum neighborhood relevancy

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Citation History

Topics

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