Abstract
One of the most usual ways of classifying the elements of a set is to cluster them according to some kind of “proximity measure”. Proximity is a topological concept and therefore it is natural to ask for topological structures that lead to cluster methods.
Using this idea, we construct some families of cluster methods starting on from a kind of V D-spaces.
In order to relate the elements of these families, morphisms between cluster methods are defined.
Research partially supported by the DGICYT, project n. PS.87-0108
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© 1991 Springer-Verlag Berlin Heidelberg
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Jacas, J., Recasens, J. (1991). A topological approach to some cluster methods. In: Bouchon-Meunier, B., Yager, R.R., Zadeh, L.A. (eds) Uncertainty in Knowledge Bases. IPMU 1990. Lecture Notes in Computer Science, vol 521. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0028134
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DOI: https://doi.org/10.1007/BFb0028134
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