结合平行坐标图的多维数据可视化散点图选择技术

Ayaka Watanabe, T. Itoh, Kazuhisa Chiba, Masahiro Kanazaki
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引用次数: 9

摘要

我们以前提出了一种可视化技术,将多维数据表示为低维平行坐标图的集合。本文提出了一种通用的可视化技术的扩展,将多维数据表示为散点图与平行坐标图的组合。我们的目标是自动选择少量的变量对,通过散点图估计它们会带来有趣的可视化。本文还介绍了该可视化技术在制造设计多目标优化中的应用。我们的多维数据可视化技术有效地帮助我们了解多目标优化过程中设计变量和目标函数的分布和相关性。
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A Scatterplots Selection Technique for Multi-dimensional Data Visualization Combining with Parallel Coordinate Plots
We have previously presented a visualization technique which represents multi-dimensional data as collection of lowdimensional parallel coordinate plots. This paper presents a general-purpose extension of the visualization technique which represents multi-dimensional data as a combination of the scatterplots with parallel coordinate plots. We aim to automatically select a small number of pairs of variables which are estimated that they bring interesting visualization by scatterplots. This paper also presents an application of this visualization technique to Multi-objective optimization of manufacturing design. Our multi-dimensional data visualization technique effectively assists us to understand the distribution and correlation of design variables and objective functions in multi-objective optimization processes.
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