| #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}")
|