AI RESEARCH
Proper Calibeating
arXiv CS.LG
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ArXi:2605.26703v1 Announce Type: cross The classic concept of "calibrated forecasts" and its recent refinement, "calibeating," are defined with respect to the standard quadratic scoring rule. We extend these notions to the class of $\textit{proper}$ scoring rules (for which the best forecast is the true distribution) and define $\textit{proper-calibration}$ and $\textit{proper-calibeating}$ by requiring the errors to converge to zero uniformly over all bounded proper scoring rules.