Visual Clustering and Classification: The Oronsay Particle Size Data Set Revisted



By

Adalbert F. X. Wilhelm


Edward J. Wegman


and

Jürgen Symanzik



ABSTRACT

Interactive statistical graphics can be effectively used to find natural groupings in observations. In this paper we want to demonstrate how clustering and classification can be done with three approaches based on highly interactive graphical environments: high-dimensional scatterplots as available in XGobi, parallel coordinate plots as available in ExplorN, and linked low-dimensional views as available in Manet. We will point out the strengths and the weaknesses of these techniques by comparing their behavior when applied to the Oronsay particle size data set.

Keywords: High Interaction Graphics, Grand Tour, Parallel Coordinate Plots, Linked Views, XGobi, ExplorN, Manet.


JOURNAL AND TECHNICAL REPORT

This Web site comes in two parts:


REFERENCES

The Oronsay particle data set has been extensively analyzed in the literature. Main references are:


DATA

You can download the Oronsay data files through this site:


ACKNOWLEDGMENTS

We would like to thank Nick Fieller for providing us with the Oronsay particle size data set (including the permission to post it on this Web site) and additional background information. Thanks are also due to Walter Olbricht for his additional comments and to Qiang Luo who assisted with the preparation of data and the analysis.



Last Update October 12, 1999