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Some Adaptive Clustering Algorithms

  • Hans-Joachim Mucha
Conference paper

Abstract

Cluster analysis attempts to detect structures in the data. Often clustering methods are incorporated into statistical software systems. Some of the most important and widely used methods are the K-means clustering and Ward’s hierarchical algorithm. But there is a lack of known successful applications.

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References

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  4. Mucha, H.-J. (1992a): Clusteranalyse mit Mikrocomputern. Akademie Verlag, BerlinGoogle Scholar
  5. Mucha, H.-J. (1992b): Specific Metrics for Cluster Analysis and Principal Components Analysis. In: Faulbaum, F. (Ed.): Soft Stat’91 Advances in Statistical Software 3. Gustav Fischer, Stuttgart, 249–258Google Scholar
  6. Mucha, H.-J. (1992c): Improvement of Stability in Cluster Analysis and PCA by Special Weighting the Variables. In: Gritzmann, P., Hettich, R., Horst, R., Sachs, E. (Eds.): Operations Research’ 91. Physica-Verlag, Heidelberg, 351–354Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  • Hans-Joachim Mucha
    • 1
  1. 1.Institute of Applied Analysis and StochasticsBerlinGermany

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