Brito, PaulaSilva, A. Pedro DuarteDias, José G.2016-06-282016-06-282015BRITO, Paula; DUARTE SILVA, A. P.; DIAS, José G. - Probabilistic Clustering of Interval Data. Intelligent Data Analysis. 1571-4128. Vol. 19, n.º 2 (2015), p. 293-3131571-4128http://hdl.handle.net/10400.14/20309In 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.engClustering methodsFinite mixture modelsInterval-valued variableIntrinsic variabilitySymbolic datajournal article10.3233/IDA-1507181088-467X84928572252000353062400006