Encyclopedia of Machine Learning and Data Mining

Living Edition
| Editors: Claude Sammut, Geoffrey I. Webb

Multi-label Learning

Living reference work entry
DOI: https://doi.org/10.1007/978-1-4899-7502-7_910-1


Multi-label learning is an important machine learning setting where each example is associated with multiple class labels simultaneously. Firstly, definition, motivation and background, and learning system structure for multi-label learning are introduced. Secondly, multi-label evaluation measures and the issue of label correlation are discussed. Thirdly, basic ideas and technical details on four representative multi-label learning algorithms are considered. Lastly, theory, extensions, and future challenges on multi-label learning are introduced.


Class Label Label Space Relevant Label Unseen Instance Label Correlation 
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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.National Key Laboratory for Novel Software TechnologyNanjing UniversityNanjing 210023China
  2. 2.School of Computer Science and EngineeringSoutheast UniversityNanjing 210096China