Comparison of different methods for determining diabetes

Mehmet Recep BOZKURT; Nilüfer YURTAY; Ziynet YILMAZ

Makale detayları

Comparison of different methods for determining diabetes

Yazarlar:

Mehmet Recep BOZKURT | Nilüfer YURTAY | Ziynet YILMAZ

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2014 Vol.22 Issue 4, pp.1044-1055

Belge Tipi:

Makale

Yayın Tarihi:

3/2014

Belge Dili:

Türkçe

Document ID (Org No.):

2000742951

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632

Özet:

 

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.

 

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.

Makale detayları

Comparison of different methods for determining diabetes

Yazarlar: Mehmet Recep BOZKURT | Nilüfer YURTAY | Ziynet YILMAZ

Yayıncı: TUBITAK

Dergi: Turkish Journal of Electrical Engineering and Computer Science 2014 Vol.22 Issue 4, pp.1044-1055

Belge Tipi: Makale

Yayın Tarihi: 3/2014

Belge Dili: Türkçe

Document ID (Org No.): 2000742951

Sıklık: İki Aylık

eISSN: 1303-6203

pISSN: 1300-0632

Sayı

Yazarlar:

Mehmet Recep BOZKURT | Nilüfer YURTAY | Ziynet YILMAZ

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2014 Vol.22 Issue 4, pp.1044-1055

Belge Tipi:

Makale

Yayın Tarihi:

3/2014

Belge Dili:

Türkçe

Document ID (Org No.):

2000742951

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632