Multi-label learning with label-specific features via weighting and label entropy guided clustering ensemble

Chunyu Zhang; Zhanshan Li

doi:10.1016/j.neucom.2020.07.107

ScienceGate Book Chapters

JOURNAL ARTICLE

Multi-label learning with label-specific features via weighting and label entropy guided clustering ensemble

Chunyu Zhang Zhanshan Li

Year: 2020 Journal: Neurocomputing Vol: 419 Pages: 59-69 Publisher: Elsevier BV

DOI: 10.1016/j.neucom.2020.07.107

Get Full-Text PDF Get Analytical Report

Keywords:

Multi-label classification Cluster analysis Artificial intelligence Computer science Weighting Pattern recognition (psychology) Entropy (arrow of time) Machine learning Set (abstract data type) Ensemble learning Data mining

Metrics

Cited By

2.50

FWCI (Field Weighted Citation Impact)

Refs

0.90

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

Spam and Phishing Detection

Physical Sciences → Computer Science → Information Systems

Web Data Mining and Analysis

Physical Sciences → Computer Science → Information Systems

Multi-label learning with label-specific features via weighting and label entropy guided clustering ensemble

Metrics

Citation History

Topics

Related Documents

Multi-Label Learning Through Label-Specific Features with Entropy Guided Clustering

Multi-label Learning with Label-Specific Features via Clustering Ensemble

Label-Specific Multi-label Classification with Entropy Guided Clustering

Multi-Label Learning Based on Label Entropy Guided Clustering

Multi-Label Learning Through Label-Specific Features with Entropy Definition