Question: Interpretaton # Make predictions y_pred = model.predict(X_test) # Evaluate the model print(confusion_matrix(y_test, y_pred)) print(classification_report(y_test, y_pred)) [[ 496 0] [ 0 2543]] precision recall f1-score support

Interpretaton # Make predictions y_pred = model.predict(X_test) # Evaluate the model print(confusion_matrix(y_test, y_pred)) print(classification_report(y_test, y_pred)) [[ 496 0] [ 0 2543]] precision recall f1-score support 0 1.00 1.00 1.00 496 1 1.00 1.00 1.00 2543 accuracy 1.00 3039 macro avg 1.00 1.00 1.00 3039 weighted avg 1.00 1.00 1.00 3039

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