Table 1.
The distribution of health insurance based on various factors.
Table 2.
Model performance metrics on imbalanced dataset.
Table 3.
Model metrics trained on data balanced by oversampling.
Table 4.
Model metrics upon balancing using SMOTE.
Fig 1.
Confusion matrices.
Fig 2.
The AUCs for the models.
Fig 3.
Variable importance from the Random Forest model.
Fig 4.
Variable importance from the XGBoost model.
Fig 5.
Variable importance from the Logistic Regression classifier.
Fig 6.
Mosaic plot.
Fig 7.
Distribution plots of predicted probabilities.