Journal
NATURE CHEMISTRY
Volume 13, Issue 6, Pages 505-508Publisher
NATURE RESEARCH
DOI: 10.1038/s41557-021-00716-z
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Funding
- National Research Foundation of Korea [4120200513611] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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In chemistry research, statistical tools based on machine learning are being integrated to train reliable, repeatable, and reproducible models. Guidelines for machine learning reports are recommended to ensure the quality of the models.
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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