Label recovery and label correlation co-learning for multi-view multi-label classification with incomplete labels

Zhifen He; Chunhua Zhang; Bin Liu; Bo Li

doi:10.1007/s10489-022-03945-y

ScienceGate Book Chapters

JOURNAL ARTICLE

Label recovery and label correlation co-learning for multi-view multi-label classification with incomplete labels

Zhifen He Chunhua Zhang Bin Liu Bo Li

Year: 2022 Journal: Applied Intelligence Vol: 53 (8)Pages: 9444-9462 Publisher: Springer Science+Business Media

DOI: 10.1007/s10489-022-03945-y

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Multi-label classification Artificial intelligence Machine learning Correlation Classifier (UML) Fuse (electrical) Binary classification Kernel (algebra) Pattern recognition (psychology) Data mining Support vector machine Mathematics

Metrics

Cited By

1.37

FWCI (Field Weighted Citation Impact)

Refs

0.79

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Text and Document Classification Technologies

Physical Sciences → Computer Science → Artificial Intelligence

Machine Learning and Data Classification

Physical Sciences → Computer Science → Artificial Intelligence

Image Retrieval and Classification Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Label recovery and label correlation co-learning for multi-view multi-label classification with incomplete labels

Metrics

Citation History

Topics

Related Documents

Multi-view Multi-label Learning with Incomplete Views and Labels

Multi-label classification with weak labels by learning label correlation and label regularization

Improved Multi-view Multi-label Learning with Incomplete Views and Labels

Multi-view multi-label learning with high-order label correlation

Class label fusion guided correlation learning for incomplete multi-label classification