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English(EN) Optimal Allocation and Volume under Surface

新框架估算ROC曲面体积和不平等性

本文介绍了一种计算临界函数集投影集合体积的新框架,特别关注最优接收者操作特征(ROC)曲面下的凸体。所提出的方法利用Aumann期望表示和Minkowski混合体积来确定ROC曲面下的体积(VUS)。研究人员开发了一种用于VUS的双重/去偏机器学习估计器,详细说明了其渐近性质和推断过程。该框架还扩展到分析不同群体之间的可行误差集,并提供了一个用于不平等测量的广义基尼系数。 AI

影响 引入了适用于机器学习的新颖统计方法,可能改进模型评估和不平等性分析。

排序理由 该条目是一篇在arXiv上发表的学术论文,详细介绍了一种新的统计框架和估计方法。[lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv stat.ML 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新框架估算ROC曲面体积和不平等性

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该条目是一篇在arXiv上发表的学术论文,详细介绍了一种新的统计框架和估计方法。[lever_c_demoted from research: ic=1 ai=0.7]
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报道来源 [1]

  1. arXiv stat.ML TIER_1 English(EN) · Kai Feng, Han Hong, Jessie Li, Wenshi Wei ·

    表面下的最优分配与体积

    arXiv:2609.38875v1 Announce Type: cross Abstract: This paper develops a framework for estimation and inference on the volumes of sets that are projections of critical function sets, focusing particularly on the convex body beneath the optimal receiver operating characteristic (RO…