Ensemble machine learning prediction of drivers affecting rice and wheat yield, greenhouse gas emissions, and yield-scaled emissions in Bangladesh

Although very preliminary, to our knowledge, this is the first attempt at ensemble machine learning applied to agricultural research and the analysis of 'big data' from farms. In addition, methods have been developed in R to graphically explore the relationships between drivers and predicted outcome...

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Detalles Bibliográficos
Autor principal: CGIAR Research Program on Climate Change, Agriculture and Food Security
Formato: Informe técnico
Lenguaje:Inglés
Publicado: 2019
Materias:
Acceso en línea:https://hdl.handle.net/10568/123019
Descripción
Sumario:Although very preliminary, to our knowledge, this is the first attempt at ensemble machine learning applied to agricultural research and the analysis of 'big data' from farms. In addition, methods have been developed in R to graphically explore the relationships between drivers and predicted outcomes using partial dependency plots.