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Compstat pp 160–165Cite as

Clustering in an Interactive Way

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Abstract

Some of the most important cluster analysis techniques are available in the interactive statistical computing environment XploRe. Furthermore, new adaptive clustering methods can be carried out. They seem to be a little bit intelligent because of their ability for learning the appropriate distance measures. Moreover, adaptive distances should also be used in order to obtain multivariate plots (Mucha 1992). In that way, both the interpretation of clustering results and highly interactive work becomes much easier.

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References

  • Härdle, W. (1990): Applied Nonparametric Regression. Cambridge University Press, Cambridge

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  • Mucha, H.-J. (1992): Clusteranalyse mit Mikrocomputern. Akademie Verlag, Berlin

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  • Mucha, H.-J., Klinke, S. (1993): Clustering Techniques in the Interactive Statistical Computing Environment Xplo-Re. Discussion Paper 9318. Institute de Statistique, Universite Catholique de Louvain, Louvain-la-Neuve

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  • Mucha, H.-J. (1994): Clustering Techniques in the Computing Environment XploRe. Proc. 17th. Annual Conference of the GfKl, Univ. of Kaiserslautern, 1993, (Eds.: Bock, H. H., Lenaki, W., and Richter, M. M.), 259–268, Springer-Verlag, Heidelberg

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  • Späth, H. (1985): Cluster Dissection and Analysis. Theory, FORTRAN Programs, Examples. Ellis Horwood Limited, Chichester

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© 1994 Springer-Verlag Berlin Heidelberg

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Mucha, HJ. (1994). Clustering in an Interactive Way. In: Dutter, R., Grossmann, W. (eds) Compstat. Physica, Heidelberg. https://doi.org/10.1007/978-3-642-52463-9_16

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  • DOI: https://doi.org/10.1007/978-3-642-52463-9_16

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-7908-0793-6

  • Online ISBN: 978-3-642-52463-9

  • eBook Packages: Springer Book Archive

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