Table 2.

Performance values for all the model.

Model	Accuracy	Precision (Class 0)	Precision (Class 1)	Recall (Class 0)	Recall (Class 1)	F1-Score (Class 0)	F1-Score (Class 1)
Logistic Regression	0.9104	0.8978	0.9125	0.8617	0.9485	0.7234	0.8918
Random Forest	0.8911	0.9108	0.9014	0.7652	0.9698	0.7439	0.9542
XGBoost	0.9251	0.9419	0.9657	0.8737	0.9672	0.7657	0.9624
SVM	0.8857	0.8194	0.8969	0.8719	0.8715	0.7412	0.8614
Neural Network	0.8757	0.8527	0.8987	0.8753	0.8982	0.7455	0.8895
K-Nearest Neighbors	0.8107	0.8414	0.8149	0.7984	0.9178	0.7085	0.8925
Decision Tree	0.8714	0.9014	0.8995	0.8679	0.9542	0.7074	0.8919
Naive Bayes	0.8347	0.7348	0.8978	0.8975	0.8849	0.7272	0.8985
AdaBoost	0.8821	0.8736	0.8784	0.7892	0.9541	0.7421	0.8938