Three-dimensional Radial Visualization of High-dimensional Continuous or Discrete Data
dc.contributor.author | Dai, Fan | |
dc.contributor.author | Zhu, Yifan | |
dc.contributor.author | Maitra, Ranjan | |
dc.contributor.department | Statistics | |
dc.date | 2019-06-30T10:02:51.000 | |
dc.date.accessioned | 2020-07-02T06:56:58Z | |
dc.date.available | 2020-07-02T06:56:58Z | |
dc.date.copyright | Tue Jan 01 00:00:00 UTC 2019 | |
dc.date.issued | 2019-01-01 | |
dc.description.abstract | <p>This paper develops methodology for 3D radial visualization of high-dimensional datasets. Our display engine is called RadViz3D and extends the classic RadViz that visualizes multivariate data in the 2D plane by mapping every record to a point inside the unit circle. The classic RadViz display has equally-spaced anchor points on the unit circle, with each of them associated with an attribute or feature of the dataset. RadViz3D 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 a better visualization than in 2D. We also propose a Max-Ratio Projection (MRP) method that 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 mixed features where a generalized distributional transform is used in conjuction with copula models before applying MRP and RadViz3D visualization.</p> | |
dc.description.comments | <p>This is a pre-print of the article Dai, Fan, Yifan Zhu, and Ranjan Maitra. "Three-dimensional Radial Visualization of High-dimensional Continuous or Discrete Data." <em>arXiv preprint arXiv:1904.06366</em> (2019). Posted with permission.</p> | |
dc.format.mimetype | application/pdf | |
dc.identifier | archive/lib.dr.iastate.edu/stat_las_pubs/174/ | |
dc.identifier.articleid | 1174 | |
dc.identifier.contextkey | 14455521 | |
dc.identifier.s3bucket | isulib-bepress-aws-west | |
dc.identifier.submissionpath | stat_las_pubs/174 | |
dc.identifier.uri | https://dr.lib.iastate.edu/handle/20.500.12876/90481 | |
dc.language.iso | en | |
dc.source.bitstream | archive/lib.dr.iastate.edu/stat_las_pubs/174/2019_MaitraRanjan_ThreeDimensional.pdf|||Fri Jan 14 21:22:21 UTC 2022 | |
dc.subject.disciplines | Statistical Methodology | |
dc.subject.disciplines | Statistics and Probability | |
dc.subject.keywords | Faces | |
dc.subject.keywords | principal components | |
dc.subject.keywords | gamma ray bursts | |
dc.subject.keywords | Indic scripts | |
dc.subject.keywords | RNA sequence | |
dc.subject.keywords | SVD | |
dc.subject.keywords | senators | |
dc.subject.keywords | suicide risk | |
dc.subject.keywords | Viz3D | |
dc.title | Three-dimensional Radial Visualization of High-dimensional Continuous or Discrete Data | |
dc.type | article | |
dc.type.genre | article | |
dspace.entity.type | Publication | |
relation.isOrgUnitOfPublication | 264904d9-9e66-4169-8e11-034e537ddbca |
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