Title: Multi-dimensional data visualisation method based on convex-corrected Radviz

Authors: Jingjing Yin; Haibo Shi; Xiaofeng Zhou; Liang Jin; Shuai Li; Yichi Zhang

Addresses: College of Information Science and Engineering, Northeastern University, Shenyang 110819, Liaoning, China; Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, Beijing, China ' Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, Liaoning, China; Key Laboratory of Network Control System, Chinese Academy of Sciences, Shenyang 110016, Liaoning, China ' Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, Liaoning, China; Key Laboratory of Network Control System, Chinese Academy of Sciences, Shenyang 110016, Liaoning, China ' Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, Liaoning, China; Key Laboratory of Network Control System, Chinese Academy of Sciences, Shenyang 110016, Liaoning, China ' Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, Liaoning, China; Key Laboratory of Network Control System, Chinese Academy of Sciences, Shenyang 110016, Liaoning, China ' Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, Liaoning, China; Key Laboratory of Network Control System, Chinese Academy of Sciences, Shenyang 110016, Liaoning, China

Abstract: Radviz is one of the most commonly used multi-dimensional data visualisation methods. Because the projection points overlap a lot in Radviz, this paper puts forward a new Radviz optimisation method to correct the position of the projected data points. Firstly, the new method introduces the Prim algorithm to realise the optimal ordering of the dimension anchors on Radviz. Secondly, the convex hull mapping and the second Radviz mapping are used to correct the position of the projected data points. Finally, the data points are visualised. In addition, in order to verify the effectiveness of the algorithm, the Dunn index was used to do a quantitative evaluation of visualisation. By comparing multiple sets of data set experiments, the results show that the new method is beneficial to obtain the better visualisation effect of multi-dimensional data in Radviz projection.

Keywords: Radviz; visualisation; multi-dimensional data; convex-corrected.

DOI: 10.1504/IJCAT.2020.107909

International Journal of Computer Applications in Technology, 2020 Vol.63 No.1/2, pp.114 - 124

Received: 09 Oct 2019
Accepted: 23 Dec 2019
Published online: 30 Jun 2020 *

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