Feature selection for multi-label learning with missing labels

Chenxi Wang; Yaojin Lin; Jinghua Liu

doi:10.1007/s10489-019-01431-6

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Feature selection for multi-label learning with missing labels

Chenxi Wang Yaojin Lin Jinghua Liu

Year: 2019 Journal: Applied Intelligence Vol: 49 (8)Pages: 3027-3042 Publisher: Springer Science+Business Media

DOI: 10.1007/s10489-019-01431-6

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Keywords:

Computer science Feature selection Artificial intelligence Preprocessor Entropy (arrow of time) Minimum redundancy feature selection Dimensionality reduction Mutual information Feature (linguistics) Curse of dimensionality Pattern recognition (psychology) Feature vector Machine learning Ambiguity Redundancy (engineering) Feature learning Data mining

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Text and Document Classification Technologies

Physical Sciences → Computer Science → Artificial Intelligence

Machine Learning in Bioinformatics

Life Sciences → Biochemistry, Genetics and Molecular Biology → Molecular Biology

Image Retrieval and Classification Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Feature selection for multi-label learning with missing labels

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