---

from sklearn.metrics import accuracy_score, classification_report


def evaluate_model(model, X_test, y_test):
    """Оценивает качество модели."""

    predictions = model.predict(X_test)

    accuracy = accuracy_score(y_test, predictions)

    print(f"\nAccuracy: {accuracy:.3f}\n")

    print(classification_report(y_test, predictions))

    print("\nFeature importance:\n")

    importance = sorted(
        zip(FEATURES, model.feature_importances_),
        key=lambda x: x[1],
        reverse=True,
    )

    for feature, score in importance:
        print(f"{feature:<35} {score:.3f}")