Comparative and complementary use of Bayesian inference and supervised learning for predictive modeling of coffee rust incidence among Kenyan smallholder farmers
Fig 5
Calibration curves for supervised learning models.
The diagonal dashed line represents perfect calibration. Brier scores: Logistic Regression (0.182), CatBoost (0.189), Random Forest (0.194), LightGBM (0.195), XGBoost (0.197), SVM (0.199), Naive Bayes (0.208), ANN (0.215).