Adaptable Radial Axes Plots for Improved Multivariate Data Visualization
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Date
2017
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association and John Wiley & Sons Ltd.
Abstract
Radial axes plots are multivariate visualization techniques that extend scatterplots in order to represent high-dimensional data as points on an observable display. Well-known methods include star coordinates or principal component biplots, which represent data attributes as vectors that de ne axes, and produce linear dimensionality reduction mappings. In this paper we propose a hybrid approach that bridges the gap between star coordinates and principal component biplots, which we denominate adaptable radial axes plots . It is based on solving convex optimization problems where users can: (a) update the axis vectors interactively, as in star coordinates, while producing mappings that enable to estimate attribute values optimally through labeled axes, similarly to principal component biplots; (b) use different norms in order to explore additional nonlinear mappings of the data; and (c) include weights and constraints in the optimization problems for sorting the data along one axis. The result is a exible technique that complements, extends, and enhances current radial methods for data analysis.
Description
@article{10.1111:cgf.13196,
journal = {Computer Graphics Forum},
title = {{Adaptable Radial Axes Plots for Improved Multivariate Data Visualization}},
author = {Rubio-Sánchez, Manuel and Sanchez, Alberto and Lehmann, Dirk J.},
year = {2017},
publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {10.1111/cgf.13196}
}