The literature on cluster analysis has a long and rich history in several different fields. In this paper, we provide an overview of the more well-known clustering methods frequently used to analyse ordinal data.We summarize and compare their main features discussing some key issues. Finally, an example of application to real data is illustrated comparing and discussing clustering performances of different methods.

Clustering Methods for Ordinal Data: A Comparison Between Standard and New Approaches / Ranalli, Monia; Rocci, Roberto. - (2015), pp. 221-228.

Clustering Methods for Ordinal Data: A Comparison Between Standard and New Approaches

Monia Ranalli;Roberto Rocci
2015

Abstract

The literature on cluster analysis has a long and rich history in several different fields. In this paper, we provide an overview of the more well-known clustering methods frequently used to analyse ordinal data.We summarize and compare their main features discussing some key issues. Finally, an example of application to real data is illustrated comparing and discussing clustering performances of different methods.
2015
Advances in Statistical Models for Data Analysis
978-3-319-17376-4
EM algorithm; finite mixture models; k-means; ordinal data; pairwise likelihood
02 Pubblicazione su volume::02a Capitolo o Articolo
Clustering Methods for Ordinal Data: A Comparison Between Standard and New Approaches / Ranalli, Monia; Rocci, Roberto. - (2015), pp. 221-228.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1348156
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