Summary
The new statistical approach to unsupervised pattern classification, developed in this paper, consists to extending the multivalue morphological concepts to multidimensional functions in order to detect the modes of the underlying probability density function, particularly when no a priori information is available as to the number of clusters and their distribution.
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© 1996 Springer-Verlag Berlin · Heidelberg
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Sbihi, A., Postaire, JG. (1996). Mode Extraction by Multivalue Morphology for Cluster Analysis. In: Gaul, W., Pfeifer, D. (eds) From Data to Knowledge. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-79999-0_21
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DOI: https://doi.org/10.1007/978-3-642-79999-0_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-60354-2
Online ISBN: 978-3-642-79999-0
eBook Packages: Springer Book Archive