Grammar-based Fuzzy Pattern Trees for Classification Problems

Aidan Murphy, Muhammad Sarmad Ali, Douglas Mota Dias, Jorge Amaral, Enrique Naredo, Conor Ryan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper introduces a novel approach to induce Fuzzy Pattern Trees (FPT) using Grammatical Evolution (GE), FGE, and applies to a set of benchmark classification problems. While conventionally a set of FPTs are needed for classifiers, one for each class, FGE needs just a single tree. This is the case for both binary and multi-classification problems. Experimental results show that FGE achieves competitive and frequently better results against state of the art FPT related methods, such as FPTs evolved using Cartesian Genetic Programming (FCGP), on a set of benchmark problems. While FCGP produces smaller trees, FGE reaches a better classification performance. FGE also benefits from a reduction in the number of necessary userselectable parameters. Furthermore, in order to tackle bloat or solutions growing too large, another version of FGE using parsimony pressure was tested. The experimental results show that FGE with this addition is able to produce smaller trees than those using FCGP, frequently without compromising the classification performance.

Original languageEnglish
Title of host publicationProceedings of the 12th International Joint Conference on Computational Intelligence, IJCCI 2020
EditorsJuan Julian Merelo, Jonathan Garibaldi, Christian Wagner, Thomas Bäck, Kurosh Madani, Kevin Warwick
PublisherScience and Technology Publications, Lda
Pages71-80
Number of pages10
ISBN (Electronic)9789897584756
ISBN (Print)9789897584756
DOIs
Publication statusPublished - 2020
Event12th International Joint Conference on Computational Intelligence, IJCCI 2020 - Budapest, Hungary
Duration: 2 Nov 20204 Nov 2020

Publication series

NameInternational Joint Conference on Computational Intelligence
Volume1
ISSN (Electronic)2184-3236

Conference

Conference12th International Joint Conference on Computational Intelligence, IJCCI 2020
Country/TerritoryHungary
CityBudapest
Period2/11/204/11/20

Keywords

  • Fuzzy Logic
  • Grammatical Evolution
  • Pattern Trees

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