Maximum Resolution Topology for Multi-Attribute Dichotomies

Article type: Research Article

Authors: Ho, James K. | Chu, Sydney C.K.

Affiliations: Information & Decision Sciences, College of Business Administration, University of Illinois at Chicago, Chicago, IL 60091 USA, e-mail: jimho@uic.edu | Operations Research Group, Department of Mathematics, University of Hong Kong, Hong Kong SAR, China, e-mail: schu@hku.hk

Abstract: The Star Plot approach to high-dimensional data visualization is applied to multi-attribute dichotomies. It is observed that the areas of the plot for the two parts of a dichotomy may be used as an aggregate measure of their relative dominance. An optimization model is developed to determine a topology (or weighted configuration of the attributes) that maximizes the resolution of this measure with respect to a given set of reference dichotomies.

Keywords: multi-attribute dichotomy, data visualization, aggregate measure, value function, optimization, exploratory data analysis, data mining

Journal: Informatica, vol. 16, no. 4, pp. 557-570, 2005