A comparison among accuracy of KNN, PNN, KNCN, DANN and NFL
Accuracy of classifications methods from Satellite
and iris imagery dataset are very important for eco-environment
monitoring and iris type classification sequentially. It is tried to
implement classifying methods on some given data files and in
this article the results and accuracies among KNN, PNN, KNCN,
DANN and NFL methods are compared.The results respectively
show that the overall accuracies of each data are approximately
%87.70 , %84.80 , %93.88, %80.70 and %80.95 .It is indicating
that the KNCN and KNN classifiers have greatly better
accuracies than the other mentioned methods which leads to
conclusion that KNCN is the best among these five classification
methods with 96.67% for iris data set and 91.09% for satellite
image dataset.
Keywords: Classification; KNN; PNN; KNCN; DANN; NFL
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ABOUT THE AUTHORS
Jamshid Tamouk
Computer Engineering Department, E.M.U University
Farshid Allahakbari
Electrical and Electronic Department, E.M.U University
Jamshid Tamouk
Computer Engineering Department, E.M.U University
Farshid Allahakbari
Electrical and Electronic Department, E.M.U University