Multi-label learning with missing and completely unobserved labels

DOI10.1007/s10618-021-00743-xzbMath1473.68148OpenAlexW3137983627MaRDI QIDQ2036751

Jun Huang, Linchuan Xu, Jing Wang, Kenji Yamanishi, Kun Qian

Publication date: 30 June 2021

Published in: Data Mining and Knowledge Discovery (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10618-021-00743-x

zbMATH Keywords

multi-label learningmissing labelscompletely unobserved labelsdiscovering new labelsunseen labels

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05) Missing data (62D10)

Uses Software

• MULAN
• ML-KNN

Cites Work

• Unnamed Item
• A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
• ML-KNN: A lazy learning approach to multi-label learning
• Multilabel classification via calibrated label ranking
• Improving multi-label classification with missing labels by learning label-specific features
• Dynamic principal projection for cost-sensitive online multi-label classification