摘要翻译：
利用Murtagh(2004b)新近提出的方法，描述了n个数据点的所有树图的空间，并将其与具有穿孔的p-adic黎曼球的模空间联系起来，提出了从p-adic几何的观点进行聚类分析的概念框架。该方法将树状图作为子树嵌入到与p-adic数相关的Bruhat-Tits树中，并追溯到Cornelissen等人。（2001）在p-adic几何中。在解释定义的基础上，在模空间的背景下讨论了分类器的概念，并给出了树图中隐顶点个数的上界。
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英文标题：
《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：
  A conceptual framework for cluster analysis from the viewpoint of p-adic geometry is introduced by describing the space of all dendrograms for n datapoints and relating it to the moduli space of p-adic Riemannian spheres with punctures using a method recently applied by Murtagh (2004b). This method embeds a dendrogram as a subtree into the Bruhat-Tits tree associated to the p-adic numbers, and goes back to Cornelissen et al. (2001) in p-adic geometry. After explaining the definitions, the concept of classifiers is discussed in the context of moduli spaces, and upper bounds for the number of hidden vertices in dendrograms are given.
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PDF链接：
https://arxiv.org/pdf/707.4072