Machine Learning in Environmental Research: Common Pitfalls and Best Practices

Zhu, Jun-Jie; Yang, Meiqi; Ren, Zhiyong Jason

doi:10.1021/acs.est.3c00026

Machine Learning in Environmental Research: Common Pitfalls and Best Practices

Journal Article · 29 June 2023 · Environmental Science and Technology

DOI:https://doi.org/10.1021/acs.est.3c00026· OSTI ID:2418770

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Department of Civil and Environmental Engineering and Andlinger Center for Energy and the Environment, Princeton University, Princeton, New Jersey 08544, United States; OSTI
Department of Civil and Environmental Engineering and Andlinger Center for Energy and the Environment, Princeton University, Princeton, New Jersey 08544, United States

Not provided.

Research Organization:: Princeton Univ., NJ (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE)

DOE Contract Number:: EE0009269

OSTI ID:: 2418770

Journal Information:: Environmental Science and Technology, Journal Name: Environmental Science and Technology Journal Issue: 46 Vol. 57; ISSN 0013-936X

Publisher:: American Chemical Society (ACS)

Country of Publication:: United States

Language:: English

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