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Activity Number:
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344
- Student Paper Award and John M. Chambers Statistical Software Award
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Type:
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Topic-Contributed
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Date/Time:
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Thursday, August 12, 2021 : 10:00 AM to 11:50 AM
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Sponsor:
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Section on Statistical Computing
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Abstract #317103
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Title:
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Three-Dimensional Radial Visualization of High-Dimensional Data Sets with Mixed Features
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Author(s):
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Yifan Zhu* and Fan Dai and Ranjan Maitra
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Companies:
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Iowa State University and Michigan Technological University and Iowa State University
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Keywords:
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Principal components;
Indic scripts;
RNA sequences;
SVD;
copula models;
generalized distributional transform
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Abstract:
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We develop methodology for three-dimensional (3D) radial visualization of high-dimensional datasets. Our display engine is calle RadViz3D and extends the classical two-dimensional (2D) RadViz (RadViz2D) that visualizes multivariate data in the (2D) plane by mapping every record to a point inside the unit circle. Our RadViz3D methodology obtains equi-spaced anchor points exactly for the five Platonic solids and approximately for the other cases via a Fibonacci grid. We show that distributing anchor points at least approximately uniformly on the 3D unit sphere provides better visualization with minimal artificial visual correlation for multivariate data with uncorrelated variables. Our Max-Ratio Projection (MRP) method then utilizes the group information in high dimensions to provide distinctive lower-dimensional projections that are then displayed using Radviz3D. Our methodology is extended to datasets with discrete and continuous features where a generalized distributional transform is used in conjunction with copula models before applying MRP and visualizing the result using RadViz3D.
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Authors who are presenting talks have a * after their name.
