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)


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.


Fuzzy Cluster Maximal Clique Partial Graph Fuzzy Intersection Overlap Cluster 
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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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