Robust classification with categorical variables

Andrea Cerioli (), Marco Riani () and Anthony C. Atkinson ()
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Andrea Cerioli: Università di Parma, Dipartimento di Economia, Sezione di Statistica e Informatica
Marco Riani: Università di Parma, Dipartimento di Economia, Sezione di Statistica e Informatica
Anthony C. Atkinson: London School of Economics, Department of Statistics

A chapter in Compstat 2006 - Proceedings in Computational Statistics, 2006, pp 507-519 from Springer

Abstract: Abstract The forward search provides a powerful and computationally simple approach for the robust analysis of multivariate data. In this paper we suggest a new forward search algorithm for clustering multivariate categorical observations. Classification based on categorical information poses a number of challenging issues that are addressed by our algorithm. These include selection of the number of groups, identification of outliers and stability of the suggested solution. The performance of the algorithm is shown with both simulated and real examples.

Keywords: Cluster analysis; forward search; dissimilarity; random starts (search for similar items in EconPapers)
Date: 2006
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-7908-1709-6_41

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DOI: 10.1007/978-3-7908-1709-6_41

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