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.
|Number of pages||5|
|Journal||CEUR Workshop Proceedings|
|State||Published - 2014|
|Event||1st Symposium on Information Management and Big Data, SIMBig 2014 - Cusco, Peru|
Duration: 8 Sep 2014 → 10 Sep 2014