TY - JOUR
T1 - 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
AU - Edward, Hinojosa C.
AU - Cesar, A. Beltran C.
PY - 2014
Y1 - 2014
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84919676071&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:84919676071
SN - 1613-0073
VL - 1318
SP - 53
EP - 57
JO - CEUR Workshop Proceedings
JF - CEUR Workshop Proceedings
T2 - 1st Symposium on Information Management and Big Data, SIMBig 2014
Y2 - 8 September 2014 through 10 September 2014
ER -