Discrete Discriminant Analysis: The Performance of Combining Models by a Hierarchical Coupling Approach

  • Ana Sousa Ferreira
  • Gilles Celeux
  • Helena Bacelar-Nicolau
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)


We are concerned with combining models in discrete discriminant analysis in the multiclass (K > 2) case. Our approach consists of decomposing the multiclass problem in several biclass problems embedded in a binary tree. The affinity coefficient (Matusita (1955); Bacelar-Nicolau (1981,1985)) is proposed for the choice of the hierarchical couples, at each level of the tree, among all possible forms of merging. For the combination of models we consider a single coefficient: a measure of the relative performance of models - the integrated likelihood coefficient (Ferreira et al., 1999)) and we evaluate its performance.


Multiclass Problem Psychological Data Vocational Identity Conditional Probability Function Kernel Discriminant Analysis 
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Copyright information

© Springer-Verlag Berlin · Heidelberg 2000

Authors and Affiliations

  • Ana Sousa Ferreira
    • 1
  • Gilles Celeux
    • 2
  • Helena Bacelar-Nicolau
    • 1
  1. 1.LEAD, Faculdade de Psicologia e Ciências da EducaçãoAlameda da UniversidadeLisboaPortugal
  2. 2.INRIA-Rhône AlpesGrenobleFrance

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