# Visualization of Labeled Mixed-featured Datasets

arXiv: https://arxiv.org/abs/1904.06366 · HTML: https://mlsanity.com/paper/1904.06366/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Apr 2019.

## Built on by (most cited first, 1 of 1)

- [A Hybrid Mixture Approach for Clustering and Characterizing Cancer Data](https://mlsanity.com/paper/2507.14380/) (2025)

## Abstract (arXiv)

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.