Abstract
Clustering as a data exploration technique is very widely applied. It is based on clustering algorithms whose usefulness depends strictly on the form and style of the incoming data. The following article comparing operator in evolutionary algorithms used to clustering of symbolic data. Clustering methods is based on list of decision rules.
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Mazur, D. (2005). Comparing Modifcation Operators Used in Clustering Algorithm Based on a Sequence of Discriminant Rules. In: Kurzyński, M., Puchała, E., Woźniak, M., żołnierek, A. (eds) Computer Recognition Systems. Advances in Soft Computing, vol 30. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32390-2_29
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DOI: https://doi.org/10.1007/3-540-32390-2_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25054-8
Online ISBN: 978-3-540-32390-7
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