# Confusion Matrix
cm = confusion_matrix(y_test, y_pred)
plt.figure(figsize=(8, 6))
sns.heatmap(cm, annot=True, fmt='d', cmap='Blues', cbar=False,
            xticklabels=['<=50K', '>50K'],
            yticklabels=['<=50K', '>50K'])
plt.xlabel('Vorhergesagt')
plt.ylabel('Tatsächlich')
plt.title('Confusion Matrix')
plt.savefig('output/Confusions_Matrix.png', dpi=300)
plt.show()

# Klassifikationsbericht
print("\nKlassifikationsbericht:")
print(classification_report(y_test, y_pred, target_names=['<=50K', '>50K']))