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Publication Detailed Description
Journal Title
Intelligent Data Analysis
Year (definitive publication)
2015
Language
English
Country
Netherlands
More Information
Web of Science®
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Abstract
In this paper we address the problem of clustering interval data, adopting a model-based approach. To this purpose, parametric models for interval-valued variables are used which consider configurations for the variance-covariance matrix that take the nature of the interval data directly into account. Results, both on synthetic and empirical data, clearly show the well-founding of the proposed approach. The method succeeds in finding parsimonious heterocedastic models which is a critical feature in many applications. Furthermore, the analysis of the different data sets made clear the need to explicitly consider the intrinsic variability present in interval data.
Acknowledgements
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Keywords
Clustering methods,Finite mixture models,Interval-valued variable,Intrinsic variability,Symbolic data
Fields of Science and Technology Classification
- Computer and Information Sciences - Natural Sciences
Funding Records
| Funding Reference | Funding Entity |
|---|---|
| PTDC/EGE-GES/103223/2008 | Fundação para a Ciência e a Tecnologia |
| PEst-OE/EGE/UI0731/2011 | Fundação para a Ciência e a Tecnologia |
| NORTE-07-0124-FEDER-000059 | Autoriadade de Gestão do Programa Operacional Regional do Norte |
| UID/GES/00315/2013 | Fundação para a Ciência e a Tecnologia |
