Cover Image
QR Code

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...

Full description

Main Author: CGIAR Research Program on Climate Change, Agriculture and Food Security
Format: Informe técnico
Language:Inglés
Published: 2019
Subjects:
research
rice
agricultural research
development
rural development
methods
data
wheat
analysis
learning
greenhouse gas emissions
farms
systems
knowledge
agrifood systems
machine learning
gas emissions
prediction
plots
Online Access:https://hdl.handle.net/10568/123019
Summary: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.

Similar Items