Multi-objective Fuzzy Pattern Trees

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@InProceedings{RodriguesdosSantos:2018:ieeeFUZZ,

• author = "Anderson {Rodrigues dos Santos} and Jorge Luis {Machado do Amaral} and Carlos Augusto {Ribeiro Soares} and Adriano {Valladao de Barros}",
• booktitle = "2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)",
• title = "Multi-objective Fuzzy Pattern Trees",
• year = "2018",
• abstract = "This paper describes a multi-objective system for induction of fuzzy classifiers based on Fuzzy Pattern Trees. Fuzzy Pattern Trees is a tree-based hierarchical model, having as internal nodes, fuzzy logical operators and their leaves are composed by the combination of fuzzy terms and input attributes. For each class present in the problem a tree is created. Each tree will be a {"}logical class description{"} allowing the interpretation of the result. The construction method of the original trees was replaced by the Cartesian Genetic Programming, to explore the search space better. Two objectives guide the search: the accuracy of the classification and the interpretability. Therefore the NSGA II multi-objective algorithm was used for search solutions that contemplate both. The proposed Classifier was compared with Random Forests, Support Vector Machines and K Nearest Neighbours in several databases of the UCI Machine Learning Repository presenting a competitive and interpretable result. Another comparison made was the proposed model, and the Fuzzy Pattern Trees initially proposed. The proposed model showed competitive results and smaller trees.",
• keywords = "genetic algorithms, genetic programming, cartesian genetic programming",
• DOI = "doi:10.1109/FUZZ-IEEE.2018.8491689",
• month = jul,
• notes = "Also known as \cite{8491689}",

}

Genetic Programming entries for Anderson Rodrigues dos Santos Jorge Luis Machado Do Amaral Carlos Augusto Ribeiro Soares Adriano Valladao de Barros

Citations