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English(EN) Isotonic Bradley-Terry Model for Paired Comparison Data

新型等渗 Bradley-Terry 模型增强配对比较分析

研究人员开发了一种新的等渗 Bradley-Terry 模型,以改进配对比较数据的分析,例如预测比赛结果和对参与者进行排名。这种新颖的模型通过交替梯度和等渗回归方法学习速率参数和反向链接函数,解决了现有 Bradley-Terry 和 Thurstone-Mosteller 模型中潜在的错误指定问题。所提出的方法确保训练误差单调改进,并通过允许精确平局来处理数据不足的情况。在足球、棒球和网球联赛的合成数据和真实数据集上进行的数值实验表明,其胜率预测和排名表现得到增强。 AI

影响 引入了一种新颖的统计建模技术,可以利用比较数据在各个领域改善预测和排名。

排序理由 该集群包含一篇关于配对比较数据新统计模型的学术论文,该论文已提交至 arXiv。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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

新型等渗 Bradley-Terry 模型增强配对比较分析

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该集群包含一篇关于配对比较数据新统计模型的学术论文,该论文已提交至 arXiv。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Ryoya Yamasaki ·

    用于配对比较数据的等渗 Bradley-Terry 模型

    arXiv:2608.02081v1 Announce Type: new Abstract: In this paper, we study prediction problems for paired comparison data, for example, predicting the win probability between two unmatched players and ranking all the players according to the order of their strengths by using win pro…