Sectors on sectors (SonS): A new hierarchical clustering visualization tool

2011 IEEE Symposium on Computational Intelligence and Data Mining (CIDM) Pub Date : 2011-04-11 DOI:10.1109/CIDM.2011.5949448

J. Martínez-Martínez, Pablo Escandell-Montero, E. Soria-Olivas, J. Martín-Guerrero, M. Martínez-Sober, J. Gómez-Sanchís

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引用次数: 5

Abstract

Clustering techniques have been widely applied to extract information from high-dimensional data structures in the last few years. Graphs are especially relevant for clustering, but many graphs associated with hierarchical clustering do not give any information about the values of the centroids' attributes and the relationships among them. In this paper, we propose a new visualization approach for hierarchical cluster analysis in which the above-mentioned information is available. The method is based on pie charts. The pie charts are divided into several pie segments or sectors corresponding to each cluster. The radius of each pie segment is proportional to the number of patterns included in each cluster. By means of new divisions in each pie sector and a color bar with as many labels as attributes, we can extract all the existing relationships among centroids' attributes at any hierarchy level. The methodology is tested in one synthetic data set and one real data set. Achieved results show the suitability and usefulness of the proposed approach.

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扇区上扇区(SonS):一种新的分层聚类可视化工具

近年来，聚类技术被广泛应用于从高维数据结构中提取信息。图与聚类特别相关，但是许多与分层聚类相关的图没有给出关于质心属性值和它们之间关系的任何信息。在本文中，我们提出了一种新的可视化方法用于分层聚类分析，其中可以获得上述信息。该方法基于饼状图。饼状图被分成几个饼段或扇区，对应于每个集群。每个饼形段的半径与每个簇中包含的模式数量成正比。通过在每个扇区中进行新的划分，并在颜色条中添加尽可能多的标签作为属性，我们可以在任何层次结构中提取质心属性之间的所有现有关系。在一个合成数据集和一个真实数据集上对该方法进行了测试。所取得的结果表明了所提出方法的适用性和有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2011 IEEE Symposium on Computational Intelligence and Data Mining (CIDM)

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