Introduction to Conformal Predictors Based on Fuzzy Logic Classifiers

  • A. Murari
  • Jesús Vega
  • D. Mazon
  • T. Courregelongue
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 382)


In this paper, an introduction to the main steps required to develop conformal predictors based on fuzzy logic classifiers is provided. The more delicate aspect is the definition of an appropriate nonconformity score, which has to be based on the membership function to preserve the specificities of Fuzzy Logic. Various examples are introduced, to describe the main properties of fuzzy logic based conformal predictors and to compare their performance with alternative approaches. The obtained results are quite promising, since conformal predictors based on fuzzy classifiers show the potential to outperform solutions based on the nearest neighbour in terms of ambiguity, robustness and interpretability


Fuzzy Logic Membership Function 


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Copyright information

© IFIP International Federation for Information Processing 2012

Authors and Affiliations

  • A. Murari
    • 1
    • 2
  • Jesús Vega
    • 3
  • D. Mazon
    • 4
  • T. Courregelongue
    • 5
  1. 1.Culham Science CentreJET-EFDAAbingdonUK
  2. 2.Consorzio RFX-Associazione EURATOM ENEA per la FusionePadovaItaly
  3. 3.Asociación EURATOM-CIEMAT para Fusión, CIEMATMadridSpain
  4. 4.Association EURATOM-CEA, CEA CadaracheSaint-Paul-lez-DuranceFrance
  5. 5.Arts et Métiers ParisTech Engineering College (ENSAM)ParisFrance

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