Exploring Common and Label-Specific Features for Multi-Label Learning With Local Label Correlations

Exploring Common and Label-Specific Features for Multi-Label Learning With Local Label Correlations

In multi-label learning, instances can be associated with a set of class labels. The existing multi-label feature selection (MLFS) methods generally adopt either of these two strategies, namely, selecting a subset of features that is shared by all labels (common features) or exploring the most discr...

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Bibliographic Details
Main Authors: Yunzhi Ling, Ying Wang, Xin Wang, Yunhao Ling
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Multi-label
feature selection
label correlations
label-specific features
Online Access:https://ieeexplore.ieee.org/document/9032184/

Internet

https://ieeexplore.ieee.org/document/9032184/

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