A case study on Morphological Data from Eimeria of Domestic Fowl using a multiobjective genetic algorithm and R&P for learning and tuning fuzzy rules for classification

Hinojosa C. Edward, A. Beltran C. Cesar

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Resumen

In this paper, we use fuzzy rule-based classification systems for classify cells of the Eimeria of Domestic Fowl based on Morphological Data. Thirteen features were extracted of the images of the cells, these features are genetically processed for learning fuzzy rules and a method reward and punishment for tuning the weights of the fuzzy rules. The experimental results show that our classifier based on interpretability fuzzy rules has a similar classification rate to that of a non-parametric and noninterpretability method.

Idioma originalInglés
Páginas (desde-hasta)53-57
Número de páginas5
PublicaciónCEUR Workshop Proceedings
Volumen1318
EstadoPublicada - 2014
Publicado de forma externa
Evento1st Symposium on Information Management and Big Data, SIMBig 2014 - Cusco, Perú
Duración: 8 set. 201410 set. 2014

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