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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| Formato: | Informe técnico |
| Lenguaje: | Inglés |
| Publicado: |
2019
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| Acceso en línea: | https://hdl.handle.net/10568/123019 |
| 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. |
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