A partitional clustering algorithm validated by a clustering tendency index based on graph theory

Authors:
Helena Brás Silva;Paula Brito;Joaquim Pinto da Costa
Affiliations:
Department of Mathematics, Polytechnic School of Engineering of Porto (ISEP), Portugal;School of Economics/LIACC, University of Porto, Portugal;Department of Applied Mathematics/FC & LIACC, University of Porto, Portugal
Venue:
Pattern Recognition
Year:
2006

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Abstract

Applying graph theory to clustering, we propose a partitional clustering method and a clustering tendency index. No initial assumptions about the data set are requested by the method. The number of clusters and the partition that best fits the data set, are selected according to the optimal clustering tendency index value.