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A Scatterplots Selection Technique for Multi-dimensional Data Visualization Combining with Parallel Coordinate Plots

机译:结合并行坐标图的多维数据可视化散点图选择技术

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We have previously presented a visualization technique which represents multi-dimensional data as collection of low-dimensional 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.
机译:我们之前已经提出了一种可视化技术,该技术将多维数据表示为低维并行坐标图的集合。本文介绍了可视化技术的通用扩展,该可视化技术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变量对,这些变量对估计它们可以通过散点图带来有趣的可视化效果。本文还介绍了该可视化技术在制造设计的多目标优化中的应用。我们的多维数据可视化技术可以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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