Fig. 12
From: Predicting tourism growth in Saudi Arabia with machine learning models for vision 2030 perspective
SHAP summary plot illustrating the relative importance and direction of feature contributions to the ensemble model’s predictions. Each dot represents an individual observation, where the horizontal axis denotes the SHAP value (impact on model output) and color intensity reflects the feature value (blue = low, red = high). Cost exhibited the highest positive contribution to tourism demand predictions, followed by Year, City, and Month, indicating that economic and temporal factors are dominant drivers in the model’s decision process.
