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Overlapping Clustering of Statistical Software Packages for PC

  • Rainer Lasch
Conference paper
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)

Summary

Cluster analysis is specially concerned with algorithms for computing non-overlapping classifications, for example partitions or hierarchies, on given object sets. For several economic problems the determination of non-overlapping classifications representing the structure of data is too specific and narrow. In opposition to that given natural overlappings should not be suppressed because the construction of overlapping clusters gives a better insight into the structure of data. In this paper several principles of constructing overlapping clusters e.g. maximal cliques, fuzzy clustering, quasi-hierarchies and pyramidal classification are presented. The advantages and disadvantages of these clumping techniques are discussed in an overlapping clustering of selected software packages.

Keywords

Fuzzy Cluster Maximal Clique Partial Graph Fuzzy Intersection Overlap Cluster 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. BAUSCH, T., BANKHOFER, U., (1992): Statistical Software Packages for PCs - A Market Survey. Statistical Papers, vol 33, 283–306. CrossRefGoogle Scholar
  2. BEZDEK, J. (1973): Fuzzy Mathematics in Pattern Classification. PhD Thesis, Cornell University, Ithaca, N.Y.Google Scholar
  3. BEZDEK, J. (1974a): Numerical taxonomy with fuzzy sets. Journal of Mathematical Biology 1, 57–74. CrossRefGoogle Scholar
  4. BEZDEK, J. (1974b): Cluster validity with fuzzy sets. Journal of Cybernetics 3, No 3,58–71. CrossRefGoogle Scholar
  5. JARDINE, N., SIBSON, R. (1971): Mathematical Taxonomy. Wiley, New York.Google Scholar
  6. LASCH, R. (1993): Pyramidaie Darstellung multivariater Daten. Josef Eul, Ber- gisch Gladbach, Köln.Google Scholar

Copyright information

© Springer-Verlag Berlin · Heidelberg 1996

Authors and Affiliations

  • Rainer Lasch
    • 1
  1. 1.Institut für Statistik und Mathematische WirtschaftstheorieUniversität AugsburgAugsburgGermany

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