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English(EN) Conformal Bayes for Two-Sided Censored Gaussian Regression under Label Shift

用于截尾高斯回归的新型保形贝叶斯方法

研究人员开发了一种名为保形贝叶斯(Conformal Bayes)的新方法,用于双侧截尾高斯回归,专门解决数据在下界和上界都被截尾时的预测挑战。该方法结合了后验预测倾斜和加权保形校准,以创建可以包含边界原子和内部区间的预测集。与现有技术相比,该方法旨在恢复边际覆盖率并产生更小的预测集,尤其是在标签偏移条件下。 AI

影响 引入了一种处理回归中截尾数据的新型统计技术,有可能提高特定机器学习应用中的预测建模准确性。

排序理由 该集群包含一篇详细介绍新统计学方法的学术论文。[lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv stat.ML 阅读 →

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用于截尾高斯回归的新型保形贝叶斯方法

报道来源 [2]

  1. arXiv stat.ML TIER_1 English(EN) · Seungjin Choi ·

    Conformal Bayes for Two-Sided Censored Gaussian Regression under Label Shift

    arXiv:2607.02173v1 Announce Type: cross Abstract: Prediction under label shift becomes nonstandard when responses are censored. In a two-sided censored Gaussian model, latent values below $L$ and above $U$ are recorded at the boundary values, so the observed predictive distributi…

  2. arXiv stat.ML TIER_1 English(EN) · Seungjin Choi ·

    Conformal Bayes for Two-Sided Censored Gaussian Regression under Label Shift

    Prediction under label shift becomes nonstandard when responses are censored. In a two-sided censored Gaussian model, latent values below $L$ and above $U$ are recorded at the boundary values, so the observed predictive distribution is mixed, with atoms at $L$ and $U$ and a conti…