Abstract
A major recurring problem in exploratory phases of data mining is the task of finding the number of clusters in a dataset. In this paper we illustrate a variant of the competitive clustering method which introduces a rival penalization mechanism, and show how it can be used to solve such problem. Additionally, we present some tests aimed at comparing the performance of our rival-penalized technique with other classical procedures.
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Borghese, A., Capraro, W. (2013). Rival-Penalized Competitive Clustering: A Study and Comparison. In: Apolloni, B., Bassis, S., Esposito, A., Morabito, F. (eds) Neural Nets and Surroundings. Smart Innovation, Systems and Technologies, vol 19. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35467-0_2
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DOI: https://doi.org/10.1007/978-3-642-35467-0_2
Publisher Name: Springer, Berlin, Heidelberg
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