Predictive Model for People Exposed to Protection Risks

Predictive Model for El Salvador People Exposed to Protection Risks

The "Predictive Model for El Salvador People Exposed to Protection Risks" is an analytical tool developed using the Gradient Boosting Machine (GBM) algorithm in R. This model aims to predict individuals or populations in El Salvador who are at a heightened risk of protection risks, such as violence or other vulnerabilities. By leveraging the GBM's ability to handle complex, non-linear relationships and interactions between variables, the model identifies key risk factors and generates predictions that can be used to inform and prioritize interventions for those most at risk. The use of GBM allows for high accuracy in predictions, making it a valuable tool for decision-makers in the humanitarian and protection cluster.