Local patterns in the form of single clusters are of interest in various areas of data mining. However, since the intention of cluster analysis is a global partition of a data set into clusters, it is not suitable to identify single clusters in a large data set where the majority of the data can not be assigned to meaningful clusters. This paper presents a new objective function-based approach to identify a single good cluster in a data set making use of techniques known from prototype-based, noise and fuzzy clustering. The proposed method can either be applied in order to identify single clusters or to carry out a standard cluster analysis by finding clusters step by step and determining the number of clusters automatically in this way.


Cluster analysis local pattern discovery 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Frank Klawonn
    • 1
  1. 1.Department of Computer ScienceUniversity of Applied Sciences Braunschweig/WolfenbuettelWolfenbuettelGermany

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