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A visualization technique for self-organizing maps with vector fields to obtain the cluster structure at desired levels of detail

机译:一种可视化技术,用于自组织带有矢量场的地图,以获得所需详细程度的聚类结构

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Self-organizing maps (SOMs) are a prominent tool for exploratory data analysis. One core task within the utilization of SOMs is the identification of the cluster structure on the map for which several visualization methods have been proposed, yet different application domains may require additional representation of the cluster structure. In this paper, we propose such a method based on pairwise distance calculation. It can be plotted on top of the map lattice with arrows that point to the closest cluster center. A parameter is provided that determines the granularity of the clustering. We provide experimental results and discuss the general applicability of our method, along with a comparison to related techniques.
机译:自组织图(SOM)是探索性数据分析的重要工具。利用SOM的一项核心任务是识别地图上的集群结构,为此已经提出了几种可视化方法,但是不同的应用领域可能需要集群结构的其他表示形式。在本文中,我们提出了一种基于成对距离计算的方法。可以使用指向最近的群集中心的箭头将其绘制在地图晶格的顶部。提供了一个参数,该参数确定群集的粒度。我们提供实验结果并讨论我们方法的一般适用性,以及与相关技术的比较。

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