arXiv stat.ML
· Papers
An analysis of binary isotonic regression: degrees of freedom and implications for calibration
arXiv:2607.27301v1 Announce Type: new Abstract: Isotonic regression is a canonical tool for estimating monotone functions and calibrating probabilistic predictors. We provide a fully sharp finite-sample characterization of its worst-case degrees of freedom on binary samples. Specifically, we identify the binary sequenc