Quantifying the impact of feature-driven shortcuts in machine learning benchmarks for circuit performance prediction
This work provides a real-data-grounded account of how a formula-driven feature dependency can still function as a practical shortcut in feature-based ML benchmarking, and offers a replicable, statistical protocol with repeated splits, effect sizes, and confidence intervals, for auditing similar dependencies in other E...