A novel framework of credit risk feature selection for SMEs during industry 4.0

With the development of industry 4.0, the credit data of SMEs are characterized by a large volume, high speed, diversity and low-value density. How to select the key features that affect the credit risk from the high-dimensional data has become the critical point to accurately measure the credit ris...

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Detalles Bibliográficos
Autores principales: Lu, Yang, Yang, Lian, Shi, Baofeng, Li, Jiaxiang, Abedin, Mohammad Zoynul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9309243/
https://www.ncbi.nlm.nih.gov/pubmed/35910041
http://dx.doi.org/10.1007/s10479-022-04849-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9309243/
https://www.ncbi.nlm.nih.gov/pubmed/35910041
http://dx.doi.org/10.1007/s10479-022-04849-3

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