Abstract
In this paper we address the problem of clustering when for each unit the available response is a smooth function. We propose a novel approach based on a landmark description which takes into account the shape of each function and suggest also a graph-like representation which can help in the classification process. The method is illustrated using a real data set based on precipitation records.
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Ingrassia, S., Cerioli, A., Corbellini, A. (2003). Some Issues on Clustering of Functional Data. In: Schader, M., Gaul, W., Vichi, M. (eds) Between Data Science and Applied Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18991-3_6
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DOI: https://doi.org/10.1007/978-3-642-18991-3_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40354-8
Online ISBN: 978-3-642-18991-3
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