Multi-label feature selection considering label importance-weighted relevance and label-dependency redundancy

Xi Ao Ma; Haibo Liu; Yi Liu; Justin Zuopeng Zhang

doi:10.1016/j.ejor.2024.11.038

Multi-label feature selection considering label importance-weighted relevance and label-dependency redundancy

Xi Ao Ma
, Haibo Liu
, Yi Liu
, Justin Zuopeng Zhang

Management

Producción científica: Article › revisión exhaustiva

Idioma original	English
Páginas (desde-hasta)	215-236
Número de páginas	22
Publicación	European Journal of Operational Research
Volumen	322
N.º	1
DOI	https://doi.org/10.1016/j.ejor.2024.11.038
Estado	Published - dic 1 2024

ASJC Scopus Subject Areas

General Computer Science
Modeling and Simulation
Management Science and Operations Research
Information Systems and Management

Acceder al documento

10.1016/j.ejor.2024.11.038

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title = "Multi-label feature selection considering label importance-weighted relevance and label-dependency redundancy",

keywords = "Information theory, Label importance, Machine learning, Multi-label feature selection, Uncertainty coefficient",

author = "Ma, \{Xi Ao\} and Haibo Liu and Yi Liu and Zhang, \{Justin Zuopeng\}",

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doi = "10.1016/j.ejor.2024.11.038",

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AU - Liu, Haibo

AU - Liu, Yi

AU - Zhang, Justin Zuopeng

PY - 2024/12/1

Y1 - 2024/12/1

KW - Information theory

KW - Label importance

KW - Machine learning

KW - Multi-label feature selection

KW - Uncertainty coefficient

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JO - European Journal of Operational Research

JF - European Journal of Operational Research

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