Multi-label feature selection based on max-dependency and min-redundancy

Yaojin Lin; Qinghua Hu; Jinghua Liu; Jie Duan

doi:10.1016/j.neucom.2015.06.010

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Multi-label feature selection based on max-dependency and min-redundancy

Yaojin Lin Qinghua Hu Jinghua Liu Jie Duan

Year: 2015 Journal: Neurocomputing Vol: 168 Pages: 92-103 Publisher: Elsevier BV

DOI: 10.1016/j.neucom.2015.06.010

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Keywords:

Minimum redundancy feature selection Redundancy (engineering) Feature selection Computer science Artificial intelligence Pattern recognition (psychology) Dependency (UML) Feature (linguistics) Information gain Mutual information Data mining Machine learning

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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

Multi-label feature selection based on max-dependency and min-redundancy

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