Data quantity governance for machine learning in materials science

Data-driven machine learning (ML) is widely employed in the analysis of materials structure–activity relationships, performance optimization and materials design due to its superior ability to reveal latent data patterns and make accurate prediction. However, because of the laborious process of mate...

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Detalles Bibliográficos
Autores principales: Liu, Yue, Yang, Zhengwei, Zou, Xinxin, Ma, Shuchang, Liu, Dahui, Avdeev, Maxim, Shi, Siqi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Review
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10265966/
https://www.ncbi.nlm.nih.gov/pubmed/37323811
http://dx.doi.org/10.1093/nsr/nwad125

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10265966/
https://www.ncbi.nlm.nih.gov/pubmed/37323811
http://dx.doi.org/10.1093/nsr/nwad125

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