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Brito, P., Silva, A. P. D. & Dias, J. G. (2015). Probabilistic clustering of interval data. Intelligent Data Analysis. 19 (2), 293-313
M. P. Brito et al., "Probabilistic clustering of interval data", in Intelligent Data Analysis, vol. 19, no. 2, pp. 293-313, 2015
@article{brito2015_1765608624486,
author = "Brito, P. and Silva, A. P. D. and Dias, J. G.",
title = "Probabilistic clustering of interval data",
journal = "Intelligent Data Analysis",
year = "2015",
volume = "19",
number = "2",
doi = "10.3233/IDA-150718",
pages = "293-313",
url = "http://iospress.metapress.com/content/1088-467X/"
}
TY - JOUR TI - Probabilistic clustering of interval data T2 - Intelligent Data Analysis VL - 19 IS - 2 AU - Brito, P. AU - Silva, A. P. D. AU - Dias, J. G. PY - 2015 SP - 293-313 SN - 1088-467X DO - 10.3233/IDA-150718 UR - http://iospress.metapress.com/content/1088-467X/ AB - 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. ER -
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