Visualization of Labeled Mixed-featured Datasets
Abstract
We develop methodology for visualization of labeled mixed-featured datasets. We first investigate datasets with continuous features where our Max-Ratio Projection (MRP) method 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 Gaussianized distributional transform is used in conjunction with copula models before applying MRP and visualizing the result using RadViz3D. A R package $radviz3d$ implementing our complete methodology is available.
- Publication:
-
arXiv e-prints
- Pub Date:
- April 2019
- DOI:
- 10.48550/arXiv.1904.06366
- arXiv:
- arXiv:1904.06366
- Bibcode:
- 2019arXiv190406366Z
- Keywords:
-
- Statistics - Machine Learning;
- Computer Science - Machine Learning;
- 62H25;
- 62H99;
- I.3.3
- E-Print:
- 8 pages, 6 figures