Best practices in machine learning for chemistry

Best practices in machine learning for chemistry

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.

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Bibliographische Detailangaben
Veröffentlicht in:Nature chemistry 2021-06, Vol.13 (6), p.505-508
Hauptverfasser: Artrith, Nongnuch, Butler, Keith T., Coudert, François-Xavier, Han, Seungwu, Isayev, Olexandr, Jain, Anubhav, Walsh, Aron
Format: Artikel
Sprache:eng
Schlagworte:
639/638/563/606
639/638/563/980
706/648/479
706/648/697/129
Analytical Chemistry
Best practice
Biochemistry
Chemical Sciences
Chemistry
Chemistry and Materials Science
Chemistry/Food Science
Comment
Computer Science
Inorganic Chemistry
Learning algorithms
Machine Learning
or physical chemistry
Organic Chemistry
Physical Chemistry
Reproducibility
Theoretical and
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Beschreibung
Zusammenfassung: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.
ISSN:1755-4330
1755-4349
DOI:10.1038/s41557-021-00716-z