Poplar's Waterlogging Resistance Modeling and Evaluating: Exploring and Perfecting the Feasibility of Machine Learning Methods in Plant Science.

Xie, Xuelin; Zhang, Xinye; Shen, Jingfang; Du, Kebing

Xie, Xuelin; Zhang, Xinye; Shen, Jingfang; Du, Kebing.

Afiliação

Xie X; College of Sciences, Huazhong Agricultural University, Wuhan, China.
Zhang X; Hubei Academy of Forestry, Wuhan, China.
Shen J; College of Sciences, Huazhong Agricultural University, Wuhan, China.
Du K; College of Horticulture and Forestry Sciences, Hubei Engineering Technology Research Center for Forestry Information, Huazhong Agricultural University, Wuhan, China.

Front Plant Sci ; 13: 821365, 2022.

Article em En | MEDLINE | ID: mdl-35222479

Palavras-chave

feature selection; flood disaster; machine learning; model establishment and evaluation; prediction of waterlogging tolerance

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Front Plant Sci Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China

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