arXiv Machine Learning
Sep 11

Benchmarking non-conformity score functions in conformal prediction

Conformal prediction replaces single-class predictions with prediction sets that guarantee a pre-specified coverage probability. The paper reviews properties of non‑conformity score functions, presents examples from the literature, and proposes new modifications. It introduces a method to evaluate prediction set sizes and compares different score functions, including their effectiveness for class‑conditional conformal prediction with imbalanced classes.

By Sol Erika Boman
arXiv Machine Learning
Sep 15

Noise-Adaptive Conformal Classification with Marginal Coverage

arXiv:2501.18060v2 Announce Type: replace-cross Abstract: Conformal inference provides a rigorous statistical framework for uncertainty quantification in machine learning, enabling well-calibrated pr...

By Teresa Bortolotti, Y. X. Rachel Wang, Xin Tong, Alessandra Menafoglio, Simone Vantini, Matteo Sesia
arXiv Machine Learning
Jul 9

Approximate full conformal prediction in an RKHS

arXiv:2601. 13102v3 Announce Type: replace-cross Abstract: Full conformal prediction is a framework that implicitly formulates distribution-free confidence prediction regions for a wide range of estimators.

By Davidson Lova Razafindrakoto, Alain Celisse, J\'er\^ome Lacaille
arXiv Machine Learning
Jul 1

On Optimal Data Splitting for Split Conformal Prediction

arXiv:2606. 31600v1 Announce Type: cross Abstract: Conformal prediction and its variants, including the split conformal prediction, provide a distribution-free framework for uncertainty quantification by constructing prediction intervals or sets with finite-sample coverage guarantees.

By Sayan Das, Bahram Yaghooti, Todd A. Kuffner, Soumendra N. Lahiri