Missing Labels Feature Selection Based on Multilabel Multi-scale Fusion Fuzzy Rough Sets
Author:
Affiliation:
1. Southwest Jiaotong University,School of Computing and Artificial Intelligence,Chengdu,China
Funder
National Natural Science Foundation of China
Natural Science Foundation of Sichuan Province
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10455090/10455096/10455290.pdf?arnumber=10455290
Reference25 articles.
1. Multi-dimensional multi-label classification: Towards encompassing heterogeneous label spaces and multi-label annotations
2. A unified low-order information-theoretic feature selection framework for multi-label learning
3. A Robust Multilabel Feature Selection Approach Based on Graph Structure Considering Fuzzy Dependency and Feature Interaction
4. Multi-label feature selection based on label correlations and feature redundancy
5. ROUGH FUZZY SETS AND FUZZY ROUGH SETS*
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