Abstract
Statistics is the first field of science where the notion of ultrametricity appeared outside mathematics. In fact, the particular geometric configuration of the ultrametric space finds optimal application in hierarchical cluster analysis methods. Moreover, it is interesting to consider the dual space of ultrametrics, which is induced by the “dual” ultrametric inequality, known as ultramine inequality. In this paper some properties of ultramine functions are analyzed and some algorithms are proposed to derive different ultramine approximation matrices of the dissimilarities between elements.
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Vicari, D. (2001). Ultramine Spaces in Classification. In: Borra, S., Rocci, R., Vichi, M., Schader, M. (eds) Advances in Classification and Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-59471-7_13
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DOI: https://doi.org/10.1007/978-3-642-59471-7_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-41488-9
Online ISBN: 978-3-642-59471-7
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