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Fixing Parameters in the Constrained Hierarchical Classification Method: Application to Digital Image Segmentation

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Book cover Classification, Clustering, and Data Mining Applications

Abstract

We analyse the parameter influence of the likelihood of the maximal link criteria family (LLA hierarchical classification method) in the context of the CAHCVR algorithm (Classification Ascendante Hiérarchique sous Contrainte de contiguïté et par agrégation des Voisins Réciproques). The results are compared to those obtained with the inertia criterion (Ward) in the context of digital image segmentation. New strategies concerning multiple aggregation in the class formation and contiguity notion are positively evaluated in terms of algorithmic complexity.

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References

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Author information

Authors and Affiliations

  1. Ecole Supérieure des Sciences Commerciales d’Angers, France

    Kaddour Bachar

  2. IRISA-Université de Rennes 1, France

    Israël-César Lerman

Authors
  1. Kaddour Bachar
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  2. Israël-César Lerman
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Editor information

Editors and Affiliations

  1. Leanna House Institute of Statistics and Decision Sciences, Duke University, 27708, Durham, NC, USA

    David Banks

  2. Department of Mathematics, Illinois Institute of Technology, 10 West 32nd Street, 60616-3793, Chicago, IL, USA

    Frederick R. McMorris

  3. Faculty of Management, Rutgers University, 180 University Avenue, 07102-1895, Newark, NJ, USA

    Phipps Arabie

  4. Institute of Decision Theory, University of Karlsruhe, Kaiserstr. 12, 76128, Karlsruhe, Germany

    Wolfgang Gaul

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© 2004 Springer-Verlag Berlin Heidelberg

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Bachar, K., Lerman, IC. (2004). Fixing Parameters in the Constrained Hierarchical Classification Method: Application to Digital Image Segmentation. In: Banks, D., McMorris, F.R., Arabie, P., Gaul, W. (eds) Classification, Clustering, and Data Mining Applications. Studies in Classification, Data Analysis, and Knowledge Organisation. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17103-1_10

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  • DOI: https://doi.org/10.1007/978-3-642-17103-1_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22014-5

  • Online ISBN: 978-3-642-17103-1

  • eBook Packages: Springer Book Archive

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