Results

The Hybrid model achieved an accuracy of 81%, nearly matching the classical Random Forest (81.7%), while the pure quantum VQC reached 75.5%. Although the Hybrid model did not surpass the classical baseline in accuracy, it maintained comparable performance while being significantly faster to run than the pure quantum VQC, demonstrating that combining quantum feature extraction with classical classifiers can be a practical middle ground.