Map-TreeMaps:层次和拓扑聚类的新方法

Hanene Azzag, M. Lebbah, A. Arfaoui
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引用次数: 0

摘要

本文提出了一种新的聚类方法,它提供了层次聚类的自组织。该方法表示原始树木森林上的大型数据集,这些数据集使用树图表示法投影在简单的二维几何关系上。获得的分区由树映射的映射表示,树映射定义了数据树。在本文中,我们提供了通过数据之间的距离来构建节点/数据树的规则,以确定节点的连接位置。本文给出并讨论了基于UCI存储库中的合成数据集和真实数据集的视觉和经验结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Map-TreeMaps: A New Approach for Hierarchical and Topological Clustering
We present in this paper a new clustering method which provides self-organization of hierarchical clustering. This method represents large datasets on a forest of original trees which are projected on a simple 2D geometric relationship using tree map representation. The obtained partition is represented by a map of tree maps, which define a tree of data. In this paper, we provide the rules that build a tree of node/data by using distance between data in order to decide where connect nodes. Visual and empirical results based on both synthetic and real datasets from the UCI repository, are given and discussed.
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