A Prediction-Based Visual Approach for Cluster Exploration and Cluster Validation by HOV3

Authors:
Ke-Bing Zhang;Mehmet A. Orgun;Kang Zhang
Affiliations:
Department of Computing, ICS, Macquarie University, Sydney, NSW 2109, Australia;Department of Computing, ICS, Macquarie University, Sydney, NSW 2109, Australia;Department of Computer Science, University of Texas at Dallas Richardson, TX 75083-0688, USA
Venue:
PKDD 2007 Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases
Year:
2007

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Abstract

Predictive knowledge discovery is an important knowledge acquisition method. It is also used in the clustering process of data mining. Visualization is very helpful for high dimensional data analysis, but not precise and this limits its usability in quantitative cluster analysis. In this paper, we adopt a visual technique called HOV3to explore and verify clustering results with quantified measurements. With the quantified contrast between grouped data distributions produced by HOV3, users can detect clusters and verify their validity efficiently.