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Dendrogramix: A hybrid tree-matrix visualization technique to support interactive exploration of dendrograms

机译:Dendrogramix:一种混合树矩阵可视化技术,可支持树状图的交互式探索

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摘要

Clustering is often a first step when trying to make sense of a large data set. A wide family of cluster analysis algorithms, namely hierarchical clustering algorithms, does not provide a partition of the data set but a hierarchy of clusters organized in a binary tree, known as a dendrogram. The dendrogram has a classical node-link representation used by experts for various tasks like: to decide which subtrees are actual clusters (e.g., by cutting the dendrogram at a given depth); to give those clusters a name by inspecting their content; etc. We present Dendrogramix, a hybrid tree-matrix interactive visualization of dendrograms that superimposes the relationship between individual objects on to the hierarchy of clusters. Dendrogramix enables users to do tasks which involve both clusters and individual objects that are impracticable with the classical representation, like: to explain why a particular objects belongs to a particular cluster; to elicit and understand uncommon patterns (e.g., objects that could have been classified in a totally different cluster); etc. Those sensemaking tasks are supported by a consistent set of interaction techniques that facilitates the exploration of large clustering results.
机译:尝试理解大型数据集时,群集通常是第一步。广泛的群集分析算法家族,即层次聚类算法,不提供数据集的分区,而是提供以二叉树形式组织的聚类层次结构,称为树状图。树状图具有经典的节点链接表示形式,专家可将其用于各种任务,例如:确定哪些子树是实际的群集(例如,通过在给定深度处切割树状图);通过检查它们的内容来命名这些集群;等。我们提出Dendrogramix,树状图的混合树矩阵交互可视化,它将单个对象之间的关系叠加到聚类的层次结构上。 Dendrogramix使用户能够执行既涉及集群又涉及单个对象的任务,而这些任务对于经典表示来说是行不通的,例如:解释特定对象为何属于特定集群;引起并理解不常见的模式(例如,可能已经被分类为完全不同的集群的对象);这些有意义的任务得到了一套一致的交互技术的支持,这些交互技术有助于探索大型聚类结果。

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