Multi-Label Attribute Reduction Based on Variable Precision Fuzzy Neighborhood Rough Set

Multi-Label Attribute Reduction Based on Variable Precision Fuzzy Neighborhood Rough Set

Multi-label attribute reduction as a common dimensionality reduction technique has obtained widely research in recent years. Most existing multi-label attribute reduction methods adopt discretization to deal with mixed data and have strict requirements on the condition of sample classification. Howe...

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Bibliographic Details
Main Authors: Panpan Chen, Menglei Lin, Jinghua Liu
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Attribute reduction
multi-label learning
rough set model
fuzzy neighborhood
variable precision
Online Access:https://ieeexplore.ieee.org/document/9144202/

Internet

https://ieeexplore.ieee.org/document/9144202/

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