A preliminary study to apply the Quine McCluskey algorithm for fuzzy rule base minimization

The Fuzzy Rule-Based Classification Systems (FR-BCS) are classification models that use fuzzy rules to represent knowledge. FBRCS are popular today, with numerous applications and studies of their behavior and efficiency. This work is dedicated to studying a method that allows the minimization of FB...

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Bibliographic Details
Published inIEEE International Fuzzy Systems conference proceedings pp. 1 - 6
Main Authors Jara, Leonardo, Gonzalez, Antonio, Perez, Raul
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2020
Subjects
Classification problems
Fuzzy rules
Interpretability
XAI
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ISSN1558-4739
DOI10.1109/FUZZ48607.2020.9177739

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Summary:The Fuzzy Rule-Based Classification Systems (FR-BCS) are classification models that use fuzzy rules to represent knowledge. FBRCS are popular today, with numerous applications and studies of their behavior and efficiency. This work is dedicated to studying a method that allows the minimization of FBRCS generated by the Chi Algorithm, using the Quine-McCluskey method so that the number of generated rules can be reduced, without greatly altering the accuracy, thus improving the simplicity of the model.
ISSN:1558-4739
DOI:10.1109/FUZZ48607.2020.9177739