Forecasting food insecurity with machine learning using data from the WFP

17 Mar 2023 — Scientists are presenting a tool that can forecast food insecurity 30 days in advance for countries with insufficient food consumption using the eXtreme Gradient Boosting (XGBoost) algorithm – a machine learning technique using several models at once for a better output. The researchers, from the Central European University, Vienna, Austria, use data from the World Food Programme (WFP) and argue that the tool might help prevent food insecurity.