Dynamic clustering for interval data based on L2 distance

Authors:
Francisco De Carvalho;Paula Brito;Hans-Hermann Bock
Affiliations:
Centro de Informática-CIn/UFPE, Av. Prof. Luiz Freire, s/n, Cidade Universitária, Recife-PE, Brasil CEP: 50740-540;Faculdade de Economia/NIAAD-LIACC, Universidade do Porto, Porto, Portugal 4200-464;Institute of Statistics, RWTH Aachen University, Aachen, Germany 52056
Venue:
Computational Statistics
Year:
2006

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Abstract

This paper introduces a partitioning clustering method for objects described by interval data. It follows the dynamic clustering approach and uses and L 2 distance. Particular emphasis is put on the standardization problem where we propose and investigate three standardization techniques for interval-type variables. Moreover, various tools for cluster interpretation are presented and illustrated by simulated and real-case data.