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1 2009

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Bacelar-Nicolau H., Nicolau F. F., Sousa A., Bacelar-Nicolau L.

Biocybernetics and Biomedical Engineering

2009

Vol. 29, no. 2

9-18

Cluster analysis or classification usually concerns a set of exploratory multivariate data analysis methods and techniques for finding a clustering structure on a dataset. That may refer either to groups of statistical data units or to groups of variables. In this work we deal with a generalization of this paradigm concerning clustering of complex data described by three different types of variables, frequently present in a three-way context. We obtain compatible versions of the same affinity coefficient for measuring similarity between statistical data units described by those three types of variables. A global generalized similarity coefficient is analyzed for such kind of mixed data, often arising in data mining or knowledge mining.