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Korzeniewski Jerzy (University of Lodz, Poland)
An Entropy Based Non-Wrapper Approach for Choosing Variables in Cluster Analysis
Metoda wybierania zmiennych w analizie skupień oparta na entropii niezależna od metody grupowania
Acta Universitatis Lodziensis. Folia Oeconomica, 2011, t. 255, s. 161-165, bibliogr. 7 poz.
Issue title
Methodological Aspects of Multivariate Statistical Analysis : Statistical Models and Applications
Analiza skupień, Entropia, Rozkłady normalne
Cluster analysis, Entropy, Normal distribution
summ., streszcz.
W artykule badamy sprawność algorytmu wybierania zmiennych w analizie skupień opartego na entropii (por. Dash. Liu. 2000). Ocena oparta jest na eksperymencie, w którym zbiory generowane są w postaci mieszanin rozkładów normalnych. Wyniki wskazują na to. że metoda nie radzi sobie tak dobrze jak to sugerowali Autorzy. (abstrakt oryginalny)

In the paper, we investigate the efficiency of an algorithm for the choice of variables in cluster analysis built on the entropy approach (Dash, Liu, 2000). The assessment of this algorithm is carried out on synthetic data sets in the form of the mixtures of normal distributions. It turns out that the method is not working so well as the Authors of the entropy based approach suggested. (original abstract)
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Full text
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  2. Carmone F. J. Jr., Kara Ali, Maxwell S. (1999). HINoV: A New Model to Improve Market Segment Definition by Identifying Noisy Variables . Journal of Marketing Research. Vol. 36. No. 4.
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  6. Steinley D., Henson R. (2005) OCLUS: An analytic method for generating clusters with known overlap. Journal of Classification. 22.
  7. Steinley D., Brusco M. (2007). A new variable weighting and selection procedure for K-means cluster analysis. Psychometrika 66
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