Credit Risk Assessment of Heavy-Polluting Enterprises: A Wide-<i>ℓ<sub>p</sub> Penalty</i> and Deep Learning Approach

Credit Risk Assessment of Heavy-Polluting Enterprises: A Wide-<i>ℓ<sub>p</sub> Penalty</i> and Deep Learning Approach

Effective credit risk assessment of heavy-polluting enterprises can achieve a balance between environmental and economic benefits. It requires the consideration of risk indicators for both the carbon information dimension and the compliance dimension. However, as the feature dimensions of the model...

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Bibliographic Details
Main Authors:	Wanying Song, Jian Min, Jianbo Yang
Format:	Article
Language:	English
Published:	MDPI AG 2023-08-01
Series:	Mathematics
Subjects:	wide and deep learning <i>ℓ<sub>p</sub> Penalty</i> feature selection non-integer regularization credit risk assessment
Online Access:	https://www.mdpi.com/2227-7390/11/16/3462

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