Partial Classifier Chains with Feature Selection by Exploiting Label Correlation in Multi-Label Classification

Partial Classifier Chains with Feature Selection by Exploiting Label Correlation in Multi-Label Classification

Multi-label classification (MLC) is a supervised learning problem where an object is naturally associated with multiple concepts because it can be described from various dimensions. How to exploit the resulting label correlations is the key issue in MLC problems. The classifier chain (CC) is a well-...

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Bibliographic Details
Main Authors: Zhenwu Wang, Tielin Wang, Benting Wan, Mengjie Han
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Entropy
Subjects:
multi-label classification
classifier chains
label correlation
feature selection
Online Access:https://www.mdpi.com/1099-4300/22/10/1143

Internet

https://www.mdpi.com/1099-4300/22/10/1143

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