Author

Sarel Cohen

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Book Open access Sep 2026

Quantum-Inspired Feature Engineering For Logistic Regression

Banks predict credit default with Logistic Regression because regulators can read its coefficients—but it cannot express interactions. We add the missing non-linearity with a quantum-inspired feature map: 8 of the data's 23 columns become rotation angles of 8 qubits in an IQP circuit simulated in PennyLane, and 2 × 8 =...

Menachem Finkelstein, Diana Levy, Sarel Cohen et al. · Proceedings of the 19th ACM... · 0 citations

#machine learning Preprint Sep 2026

Quantum Feature Engineering for Credit Default Prediction: When and Why IQP Circuits Help Linear Classifiers

It is shown that how the 8 input features are chosen matters: Random Forest importance-guided selection reaches F1 = 0.523, while encoding maximally uncorrelated features drops it to 0.496, demonstrating that the circuit amplifies informative structure rather than creating it from scratch.

Menachem Finkelstein, Diana Levy, Z. Yakhini et al. · 0 citations