2017•Unpublished venueRequires access

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

Ayaka Watanabe, Takayuki Itoh, Kazuhisa Chiba, Masahiro Kanazaki

Open publisher page 10 citations

Abstract

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.

About this research paper

What this paper is about

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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OpenAlex reports 10 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

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.

Key concepts: Visualization, Parallel coordinates, Computer science, Data visualization, Information visualization, Scatter plot, Data mining, Multidimensional data

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