A probabilistic model for case-based reasoning

  • Andrés F. Rodriguez
  • Sunil Vadera
  • L. Enrique Sucar
Scientific Papers CBR And Uncertainty
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1266)


An exemplar-based model with foundations in Bayesian networks is described. The proposed model utilises two Bayesian networks: one for indexing of categories, and another for identifying exemplars within categories. Learning is incrementally conducted each time a new case is classified. The representation structure dynamically changes each time a new case is classified and a coverage function is used as a basis for selecting suitable exemplars. Finally, a simple example is given to illustrate the concepts in the model.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Andrés F. Rodriguez
    • 1
  • Sunil Vadera
    • 1
  • L. Enrique Sucar
    • 2
  1. 1.Department of Mathematics and Computer ScienceUniversity of SalfordSalford
  2. 2.ITESM - Campus MorelosMor.Mexico

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