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Interactive Exploratory Data Analysis

, , , and . Proceedings of the 2004 IEEE Congress on Evolutionary Computation, page 1098--1104. Portland, Oregon, IEEE Press, (20-23 June 2004)

Abstract

We illustrate with two simple examples how Interactive Evolutionary Computation (IEC) can be applied to Exploratory Data Analysis (EDA). IEC is valuable in an EDA context because the objective function is by definition either unknown a priori or difficult to formalize. In the first example IEC is used to evolve the "true" metric of attribute space. The goal here is to evolve the attribute space distance function until "interesting" features of the data are revealed when a clustering algorithm is applied. In a second example, we show how a user can interactively evolve an auditory display of cluster data. In this example, we use IEC with Genetic Programming to evolve a mapping of data to sound for sonifying qualities of data clusters.

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