May 14, 2024, 4:42 a.m. | Shi-ang Qi, Yakun Yu, Russell Greiner

cs.LG updates on arXiv.org arxiv.org

arXiv:2405.07374v1 Announce Type: new
Abstract: Discrimination and calibration represent two important properties of survival analysis, with the former assessing the model's ability to accurately rank subjects and the latter evaluating the alignment of predicted outcomes with actual events. With their distinct nature, it is hard for survival models to simultaneously optimize both of them especially as many previous results found improving calibration tends to diminish discrimination performance. This paper introduces a novel approach utilizing conformal regression that can improve a …

abstract alignment analysis arxiv calibration cs.ai cs.lg discrimination events nature process stat.ml survival type

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