TY  - JOUR
TI  - Comparison of different methods for determining diabetes
AB  - In this study, the Pima Indian Diabetes dataset was categorized with 8 different classifiers. The data were taken from the University of California Irvine Machine Learning Repository's web site. As a classifier, 6 different neural networks [probabilistic neural network (PNN), learning vector quantization, feedforward networks, cascade-forward networks, distributed time delay networks (DTDN), and time delay networks], the artificial immune system, and the Gini algorithm from decision trees were used. The classifier's performance ratios were studied separately as accuracy, sensitivity, and specificity and the success rates of all of the classifiers are presented. Among these 8 classifiers, the best accuracy and specificity values were achieved with the DTDN and the best sensitivity value was achieved with the PNN.
AU  - YURTAY, Nilüfer
AU  - SERTKAYA, Cengiz
AU  - BOZKURT, MEHMET RECEP
AU  - YILMAZ, Ziynet
PY  - 2014
JO  - Turkish Journal of Electrical Engineering and Computer Sciences
VL  - 22
IS  - 4
SN  - 1300-0632
SP  - 1044
EP  - 1055
DB  - TRDizin
UR  - http://search/yayin/detay/214034
ER  -