#Compare the results in terms of accuracy, precision and recall
from sklearn.metrics import accuracy_score, precision_score, recall_score 
accuracy_log = accuracy_score(y_test, y_pred_log) 
precision_log = precision_score(y_test, y_pred_log) 
recall_log = recall_score(y_test, y_pred_log) 

accuracy_knn = accuracy_score(y_test, y_pred_knn) 
precision_knn = precision_score(y_test, y_pred_knn) 
recall_knn = recall_score(y_test, y_pred_knn) 

print("Comparison of Models:") 
print(f"{'Model':<20}{'Accuracy':<10}{'Precision':<10}{'Recall':<10}") 
print(f"{'Logistic Regression':<20}{accuracy_log:.2f}      {precision_log:.2f}      {recall_log:.2f}") 
print(f"{'KNN':<20}{accuracy_knn:.2f}      {precision_knn:.2f}      {recall_knn:.2f}")