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Grade Correspondence-cluster Analysis Applied to Separate Components of Reversely Regular Mixtures

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

Abstract

The paper presents how the method called grade correspondence-cluster analysis (GCCA) can extract data subtables, which are characterized by specifically regular, distinctly different data structures. A short review of basic ideas underlying GCCA is given in Sec. 1. A description of straight and reverse regularity of data tables transformed by the GCCA is given in Sec. 2. These concepts are illustrated on a real data example, which describes development factors and economic status of Polish small business service firms. In the next sections, this data table is analyzed and effects of the method are demonstrated.

Keywords

Small Business Data Table Regular Structure Probability Table Positive Dependence 
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

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Alicja Ciok
    • 1
    • 2
  1. 1.Institute of Computer Science PASWarsawPoland
  2. 2.Institute of Home Market and ConsumptionWarsawPoland

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