Which implementation correctly calculates the accuracy of a logistic regression model and prints a classification report?
from sklearn.metrics import accuracy_score, classification_reportaccuracy = accuracy_score(y_test, y_pred)print(f"Accuracy: {accuracy:.2f}")print(classification_report(y_test, y_pred))
from sklearn.metrics import classification_reportprint(classification_report(y_pred, y_test))print("Model evaluation complete.")
from sklearn.metrics import accuracy_score, confusion_matrixprint(f"Accuracy: {accuracy_score(y_test, y_pred)}")print(confusion_matrix(y_test, y_pred))