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The perspective-based observational tunnels method: A new method of multidimensional data visualization

机译:基于透视的观测隧道方法:多维数据可视化的新方法

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The article describes a new unique method of multidimensional data visualization. It has been developed as modified observational tunnels method, which was previously known and used many times. The modification consists in supplementing the observational tunnels method used for visualization of multidimensional data with the concept of perspective. In this way, the orientation and navigation in multidimensional space are largely facilitated. The differences in effects of observational tunnels method and perspective-based observational tunnels method have been presented. The effectiveness of the new visualization method has been compared with selected four well-known methods of multidimensional data visualization: parallel coordinates, orthogonal projection, principal component analysis, and multidimensional scaling. The research revealed that the perspective-based observational tunnels method sometimes makes it possible to obtain information about significant features of analyzed data even when other methods selected for comparative studies are not able to show it. This article includes a presentation of the views of 5-dimensional data obtained from the print recognition process, which allowed the author to state that the features chosen for the development of spatial features are, in this case, sufficient for the correct recognition process. The previously published ranking presenting seven different methods of multidimensional data visualization was supplemented with the perspective-based observational tunnels method. This ranking was conducted using 7-dimensional data describing different types of coal. Thus, it was shown that, in this case, the presented method constitutes the efficient tool among other qualitative visualization analysis methods.
机译:本文介绍了多维数据可视化的一种独特的新方法。它已被开发为改进的观测隧道方法,该方法先前已知并已被多次使用。修改内容包括使用透视图概念对用于多维数据可视化的观测隧道方法进行补充。这样,大大方便了多维空间中的定向和导航。提出了观测隧道方法与基于透视的观测隧道方法在效果上的差异。新的可视化方法的有效性已与选定的四种多维数据可视化方法进行了比较:平行坐标,正交投影,主成分分析和多维缩放。研究表明,即使选择用于比较研究的其他方法无法显示出基于透视的观测隧道方法,有时也可能获得有关分析数据重要特征的信息。本文介绍了从打印识别过程中获得的5维数据视图,该视图允许作者声明在这种情况下为发展空间特征而选择的特征足以进行正确的识别过程。先前发布的排名提供了七种不同的多维数据可视化方法,并以基于透视的观察隧道方法进行了补充。使用描述不同类型煤炭的7维数据进行此排名。因此,表明在这种情况下,所提出的方法构成了其他定性可视化分析方法中的有效工具。

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