Semi-Supervised Multi-view Multi-label Classification Based on Nonnegative Matrix Factorization

Guangxia Wang; Changqing Zhang; Pengfei Zhu; Qinghua Hu

doi:10.1007/978-3-319-68612-7_39

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Semi-Supervised Multi-view Multi-label Classification Based on Nonnegative Matrix Factorization

Guangxia Wang Changqing Zhang Pengfei Zhu Qinghua Hu

Year: 2017 Lecture notes in computer science Pages: 340-348 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-319-68612-7_39

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Keywords:

Non-negative matrix factorization Computer science Artificial intelligence Matrix decomposition Benchmark (surveying) Pattern recognition (psychology) Labeled data Set (abstract data type) Machine learning Data set Semi-supervised learning Supervised learning Data mining Artificial neural network

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Text and Document Classification Technologies

Physical Sciences → Computer Science → Artificial Intelligence

Advanced Image and Video Retrieval Techniques

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Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Semi-Supervised Multi-view Multi-label Classification Based on Nonnegative Matrix Factorization

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