Interactive bivariate mode trees for visual structure analysis

The number of modes in a kernel density estimation of a certain data distribution is strongly dependent on the chosen scale parameter. In this paper, we present an interactive mode tree visualization that allows to visually analyze the modality structure of a data distribution. Due to the branched structure of the bivariate mode tree, composed of many curved arcs in 3D, we need to utilize advanced techniques, including clutter removal through transparency, on demand outlier suppression or preservation, and best views, to improve the legibility of the visualization mapping.

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