The combined use of self-organizing maps and Andrews' Curves.
The use of self-organizing maps to analyze data often depends on finding effective methods to visualize the SOM's structure. In this paper we propose a new way to perform that visualization using a variant of Andrews' Curves. Also we show that the interaction between these two methods allows us to find sub-clusters within identified clusters. Perhaps more importantly, using the SOM to pre-process data by identifying gross features enables us to use Andrews' Curves on data sets which would have previously been too large for the methodology. Finally we show how a three way interaction between the human user and these two methods can be a valuable exploratory data analysis tool.
García-Osorio
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Applied Computational Intelligence Research Unit, The University of Paisley, Scotland. cgosorio@ubu.es
Fyfe
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D000465:Algorithms; D001185:Artificial Intelligence; D002965:Classification; D016000:Cluster Analysis; D003627:Data Interpretation, Statistical; D056890:Eukaryota / Q000145:classification; D008959:Models, Neurological