Label driven latent subspace learning for multi-view multi-label classification

Wei Liu; Jiazheng Yuan; Gengyu Lyu; Songhe Feng

doi:10.1007/s10489-022-03600-6

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Label driven latent subspace learning for multi-view multi-label classification

Wei Liu Jiazheng Yuan Gengyu Lyu Songhe Feng

Year: 2022 Journal: Applied Intelligence Vol: 53 (4)Pages: 3850-3863 Publisher: Springer Science+Business Media

DOI: 10.1007/s10489-022-03600-6

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Keywords:

Discriminative model Subspace topology Computer science Random subspace method Artificial intelligence Pattern recognition (psychology) Classifier (UML) Construct (python library) Feature (linguistics) Consistency (knowledge bases) Machine learning Feature learning Feature vector

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Text and Document Classification Technologies

Physical Sciences → Computer Science → Artificial Intelligence

Machine Learning in Bioinformatics

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Advanced Image and Video Retrieval Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Label driven latent subspace learning for multi-view multi-label classification

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