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Best practices in machine learning for chemistry

Nature chemistry, 2021-06, Vol.13 (6), p.505-508 [Peer Reviewed Journal]

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Title:
Best practices in machine learning for chemistry
Author: Artrith, Nongnuch ; Butler, Keith T. ; Coudert, François-Xavier ; Han, Seungwu ; Isayev, Olexandr ; Jain, Anubhav ; Walsh, Aron
Subjects: Best practice ; Chemical Sciences ; Computer Science ; Learning algorithms ; Machine Learning ; or physical chemistry ; Reproducibility ; Theoretical and
Is Part Of: Nature chemistry, 2021-06, Vol.13 (6), p.505-508
Description: Statistical tools based on machine learning are becoming integrated into chemistry research workflows. We discuss the elements necessary to train reliable, repeatable and reproducible models, and recommend a set of guidelines for machine learning reports.
Publisher: London: Nature Publishing Group
Language: English
Identifier: ISSN: 1755-4330
EISSN: 1755-4349
DOI: 10.1038/s41557-021-00716-z
PMID: 34059804
Source: Hyper Article en Ligne (HAL) (Open Access)
ProQuest Central

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