On unifying probabilistic/fuzzy and possibilistic rejection-based classifiers

  • Carl Frélicot
Rejection in Pattern Recognition
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1451)


This paper aims at unifying the presentation of two-fold rejectionbased pattern classifiers. We propose to define such a classifier as a couple of labelling and hardening functions which are independent in some way. Within this framework, crisp and probabilistic / fuzzy rejection-based classifiers are shown to be particular cases of possibilistic ones. Classifiers with no reject option remains particular cases of rejection-based ones. Examples of so-defined classifiers are presented and their ability to deal with the reject problem is shown on artificial and real data sets.


Hardening Function Pattern Classification Label Vector Classification Area Unit Hypercube 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Carl Frélicot
    • 1
  1. 1.Laboratoire d'Informatique et d'Imagerie IndustrielleUniversité de La RochelleLa Rochelle Cedex 1France

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