摘要翻译：
数据分析中使用的树状图是超参数空间，因此是非阿基米德几何的对象。已知树状图存在$P$-adic表示。由无穷远处的一点完成，它们可以被视为与$p$-adic射影线相关联的Bruhat-Tits树的子树。结果表明，代数几何中已知的某些模空间是树状图（族）的p-adic参数空间，随机分类也可以在此框架内进行。最后，我们计算了树图隐藏部分的拓扑结构。
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英文标题：
《Degenerating families of dendrograms》
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作者：
Patrick Erik Bradley
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最新提交年份：
2007
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分类信息：

一级分类：Statistics        统计学
二级分类：Machine Learning        机器学习
分类描述：Covers machine learning papers (supervised, unsupervised, semi-supervised learning, graphical models, reinforcement learning, bandits, high dimensional inference, etc.) with a statistical or theoretical grounding
覆盖机器学习论文（监督，无监督，半监督学习，图形模型，强化学习，强盗，高维推理等）与统计或理论基础
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英文摘要：
  Dendrograms used in data analysis are ultrametric spaces, hence objects of nonarchimedean geometry. It is known that there exist $p$-adic representation of dendrograms. Completed by a point at infinity, they can be viewed as subtrees of the Bruhat-Tits tree associated to the $p$-adic projective line. The implications are that certain moduli spaces known in algebraic geometry are $p$-adic parameter spaces of (families of) dendrograms, and stochastic classification can also be handled within this framework. At the end, we calculate the topology of the hidden part of a dendrogram.
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PDF链接：
https://arxiv.org/pdf/707.3536