# Evaluate the Random Forest model
rf_accuracy = accuracy_score(y_test, rf_pred)
rf_precision = precision_score(y_test, rf_pred)
rf_recall = recall_score(y_test, rf_pred)
rf_f1 = f1_score(y_test, rf_pred)

print("Random Forest Accuracy:", rf_accuracy)
print("Random Forest Precision:", rf_precision)
print("Random Forest Recall:", rf_recall)
print("Random Forest F1 Score:", rf_f1)

# Evaluate the SVM model
svm_accuracy = accuracy_score(y_test, svm_pred)
svm_precision = precision_score(y_test, svm_pred)
svm_recall = recall_score(y_test, svm_pred)
svm_f1 = f1_score(y_test, svm_pred)

print("SVM Accuracy:", svm_accuracy)
print("SVM Precision:", svm_precision)
print("SVM Recall:", svm_recall)
print("SVM F1 Score:", svm_f1)

        __
        __