Two novelty learning models developed based on deep cascade forest to address the environmental imbalanced issues: A case study of drinking water quality prediction.

Chen, Xingguo; Liu, Houtao; Liu, Fengrui; Huang, Tian; Shen, Ruqin; Deng, Yongfeng; Chen, Da

Chen, Xingguo; Liu, Houtao; Liu, Fengrui; Huang, Tian; Shen, Ruqin; Deng, Yongfeng; Chen, Da.

Afiliação

Chen X; Jiangsu Key Laboratory of Big Data Security & Intelligent Processing, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu, 210023, China; State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, Jiangsu, 210023, China.
Liu H; Jiangsu Key Laboratory of Big Data Security & Intelligent Processing, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu, 210023, China.
Liu F; John F. Kennedy School of Government, Harvard University, Cambridge, MA, 02138, USA.
Huang T; Jiangsu Key Laboratory of Big Data Security & Intelligent Processing, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu, 210023, China.
Shen R; School of Environment, Guangzhou Key Laboratory of Environmental Exposure and Health, And Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, Guangdong, 510632, China.
Deng Y; School of Environment, Guangzhou Key Laboratory of Environmental Exposure and Health, And Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, Guangdong, 510632, China. Electronic address: Yongfengdeng@jnu.edu.cn.
Chen D; School of Environment, Guangzhou Key Laboratory of Environmental Exposure and Health, And Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, Guangdong, 510632, China.

Environ Pollut ; 291: 118153, 2021 Dec 15.

Article em En | MEDLINE | ID: mdl-34534828

Assuntos

Água Potável; Florestas; Aprendizado de Máquina; Qualidade da Água

Palavras-chave

Cost-sensitive; Deep cascade forest; Environmental imbalance issues; Feature extraction; Feature selection

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Água Potável Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Environ Pollut Assunto da revista: SAUDE AMBIENTAL Ano de publicação: 2021 Tipo de documento: Article País de afiliação: China País de publicação: Reino Unido

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