Visual Data Mining with Parallel Coordinates

Abstract

The display of multivariate datasets in parallel coordinates, transforms the search for relations among the variables into a 2-D pattern recognition problem. This is the basis for the application to Visual Data Mining. Guidelines for Visual Data Mining are illustrated with a the scenario - of the interactions between the user and the display - are illustrated on a dataset from the production of a VLSI chip. The real strength of parallel coordinates is in modeling relations between the variables. This is shown with a simplified Economic Model constructed using data from various economic sectors of a real country. The visual model shows the interelationship and dependencies between the sectors, circumstances where there is competition for the same resource, and feasible economic policies. Interactively, the model can be used to do trade-off analyses, discover sensitivies, do approximate optimization, for monitoring (as in a Process) and Decision Support.

JEL Classification: C80