Grade Correspondence-cluster Analysis Applied to Separate Components of Reversely Regular Mixtures
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.
KeywordsSmall Business Data Table Regular Structure Probability Table Positive Dependence
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