Towards a theory of holistic clustering

A. Dress
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引用次数: 31

Abstract

In this note, cluster theory is presented from a rather abstract point of view, basic known results are reviewed from this view point, and some new results which motivated the proposed approach, as well as some new problems which naturally arise in this context, are presented. Towards a Theory of Holistic Clustering A.W.M. Dress Bielefeld, Germany Abstract: In this note, cluster theory is presented from a rather abstract point of view, basic known results are reviewed from this view point, and some new results which motivated the proposed approach, as well as some new problems which naturally arise in this context, are presented. In this note, cluster theory is presented from a rather abstract point of view, basic known results are reviewed from this view point, and some new results which motivated the proposed approach, as well as some new problems which naturally arise in this context, are presented. 1 A Local-Global Approach to Clustering Clustering procedures (as well as many other mathematical techniques) can be viewed as methods for extracting globally relevant features from locally distributed information. A rather natural, simple and sufficiently general conceptual framework for describing clustering procedures is, therefore, the following one: We assume that, for any given (generally finite) set X, we can form the set Inj (X) comprising all possible structures defined on X which encode the information regarding X we are seeking: this could be the set of all tree structures or the set of all ultrametrics definable on X, or just the set P(P(X)) of all subsets of the power set P(X) of X. In addition, we assume that, for any pair (X, Y) consisting of a set X and a subset Y of X, information regarding X implies information regarding Y which is expressed in form of a map res = resx-+Y : Inf (X)--+ Inj(Y) : i I-t ily called the restriction map (relative to X andY), and we assume consistency of restriction by requiring that, for all Z ~ Y ~ X and i E Inf(X), we have
迈向整体聚类理论
在这篇笔记中,聚类理论是从一个相当抽象的角度提出的,从这个角度回顾了基本的已知结果,并提出了一些新的结果,这些结果激发了所提出的方法,以及在这种背景下自然产生的一些新问题。摘要:本文从一个相当抽象的角度介绍了聚类理论,从这个角度回顾了一些已知的基本结果,并提出了一些推动该方法的新结果,以及在此背景下自然产生的一些新问题。在这篇笔记中,聚类理论是从一个相当抽象的角度提出的,从这个角度回顾了基本的已知结果,并提出了一些新的结果,这些结果激发了所提出的方法,以及在这种背景下自然产生的一些新问题。聚类过程(以及许多其他数学技术)可以被视为从局部分布的信息中提取全局相关特征的方法。因此,描述聚类过程的一个相当自然、简单和足够普遍的概念框架是:我们假设,对于任何给定的(一般有限的)集合X,我们可以形成集合Inj (X),它包含X上定义的所有可能的结构,这些结构编码了我们所寻找的关于X的信息:这可以是X上所有树结构的集合,也可以是X上可定义的所有超度量的集合,或者仅仅是X的幂集P(X)的所有子集的集合P(P(X))。此外,我们假设,对于任何由集合X和X的子集Y组成的对(X, Y),关于X的信息隐含着关于Y的信息,其表示形式为映射res = resx-+Y: Inf (X)- + Inj(Y):i i -t被称为约束映射(相对于X andY),我们假设约束的一致性,通过要求,对于所有Z ~ Y ~ X和i E Inf(X),我们有
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