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Conformal Predictive Systems Under Covariate Shift
April 24, 2024, 4:42 a.m. | Jef Jonkers, Glenn Van Wallendael, Luc Duchateau, Sofie Van Hoecke
cs.LG updates on arXiv.org arxiv.org
Abstract: Conformal Predictive Systems (CPS) offer a versatile framework for constructing predictive distributions, allowing for calibrated inference and informative decision-making. However, their applicability has been limited to scenarios adhering to the Independent and Identically Distributed (IID) model assumption. This paper extends CPS to accommodate scenarios characterized by covariate shifts. We therefore propose Weighted CPS (WCPS), akin to Weighted Conformal Prediction (WCP), leveraging likelihood ratios between training and testing covariate distributions. This extension enables the construction of …
abstract arxiv cs.lg decision distributed framework however independent inference making paper predictive shift stat.ml systems type
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