Skip to Main content Skip to Navigation
Conference papers

Introduction to Conformal Predictors Based on Fuzzy Logic Classifiers

Abstract : 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
Document type :
Conference papers
Complete list of metadatas

Cited literature [10 references]  Display  Hide  Download
Contributor : Hal Ifip <>
Submitted on : Tuesday, May 16, 2017 - 9:17:07 AM
Last modification on : Monday, March 30, 2020 - 8:45:50 AM
Long-term archiving on: : Friday, August 18, 2017 - 12:37:44 AM


Files produced by the author(s)


Distributed under a Creative Commons Attribution 4.0 International License



A. Murari, Jesús Vega, D. Mazon, T. Courregelongue. Introduction to Conformal Predictors Based on Fuzzy Logic Classifiers. 8th International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2012, Halkidiki, Greece. pp.203-213, ⟨10.1007/978-3-642-33412-2_21⟩. ⟨hal-01523072⟩



Record views


Files downloads