𝗕𝗲𝘁𝘁𝗲𝗿 𝗧𝗵𝗮𝗻 𝗖𝗹𝗮𝘀𝘀𝗶𝗰𝗮𝗹? 𝗛𝗼𝘄 𝘁𝗼 𝗕𝗲𝗻𝗰𝗵𝗺𝗮𝗿𝗸 𝗤𝘂𝗮𝗻𝘁𝘂𝗺 𝗠𝗟

𝗕𝗲𝘁𝘁𝗲𝗿 𝗧𝗵𝗮𝗻 𝗖𝗹𝗮𝘀𝘀𝗶𝗰𝗮𝗹? 𝗛𝗼𝘄 𝘁𝗼 𝗕𝗲𝗻𝗰𝗵𝗺𝗮𝗿𝗸 𝗤𝘂𝗮𝗻𝘁𝘂𝗺 𝗠𝗟

Testing quantum machine learning models is hard. Most people compare them to classical models. They look for speed or accuracy.

Simple comparisons often fail. Quantum hardware has noise. Classical hardware has decades of optimization. You need a better way to measure progress.

Follow these steps to benchmark correctly:

• Select fair classical baselines. Use the best existing classical algorithms.
• Account for hardware noise. Do not assume perfect quantum gates.
• Measure scalability. See how performance changes as you add qubits.
• Use specific error metrics. General accuracy is not enough for quantum systems.

Benchmarking defines the path forward for the field. If you measure wrong, you learn nothing.

Source: https://dev.to/paperium/better-than-classical-the-subtle-art-of-benchmarking-quantum-machine-learningmodels-32dp

Optional learning community: https://t.me/GyaanSetuAi