Predicting and identifying factors associated with undernutrition among children under five years in Ghana using machine learning algorithms.

The XGBoost model was the best model for predicting wasting, stunting, and underweight. The findings showed that different ML algorithms could be useful for predicting undernutrition and identifying important predictors for targeted interventions among children under five years in Ghana.