Feature selection for hybrid information systems based on fuzzy $$\beta $$ β covering and fuzzy evidence theory

Abstract Feature selection plays a crucial role in machine learning, as it eliminates data noise and redundancy, thereby significantly reducing computational complexity and enhancing the overall performance of the model. The challenges of feature selection for hybrid information systems stem from th...

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Principais autores:	Xiaoqin Ma, Huanhuan Hu, Qinli Zhang, Yi Xu
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Springer 2024-07-01
coleção:	Complex & Intelligent Systems
Assuntos:	Feature selection Fuzzy $$\beta $$ β covering Fuzzy belief Fuzzy plausibility Hybrid information systems
Acesso em linha:	https://doi.org/10.1007/s40747-024-01560-7
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