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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Hierarchical Clustering for Interval-Valued Functional Data
verfasst von : Nobuo Shimizu
Erschienen in: Intelligent Decision Technologies
Verlag: Springer Berlin Heidelberg
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In this paper, we deal with hierarchical clustering for interval-valued functional data. Functional data is defined as the data which is function, or as the data approximated as a function. Functional cluster analysis is proposed as cluster analysis for functional data. Interval-valued functional data is defined as the functional data whose range corresponding to each value in the domain is interval-valued data. Interval-valued data is typical of symbolic data, and also interval-valued functional data can be considered to be a kind of symbolic data.We propose hierarchical clustering for interval-valued functional data as the extension of functional clustering method, and apply this method to real data.