Research on Multi-Label Semi-Supervised Learning Algorithm Based on Dual Selection Criteria

Research on Multi-Label Semi-Supervised Learning Algorithm Based on Dual Selection Criteria

With the rapid development of information technology, efficient multi label classification of massive data is one of the important tasks of big data systems. Semi supervised learning algorithm is an effective data classification method, currently mainly applied to the classification of single label...

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Bibliographic Details
Main Authors: Rongxin Liu, Yufang Lu, Lei Shi, Shuru Tan
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Multi-label
semi-supervised learning
COIN structure
K-nearest neighbor algorithm
Online Access:https://ieeexplore.ieee.org/document/10445172/

Internet

https://ieeexplore.ieee.org/document/10445172/

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