DocumentCode :
3641563
Title :
Diagnosis of diabetes by using Adaptive SVM
Author :
Emre Gürbüz;Erdal Kılıç
Author_Institution :
Bilgisayar Mü
fYear :
2011
fDate :
4/1/2011 12:00:00 AM
Firstpage :
46
Lastpage :
49
Abstract :
In this study, a new Support Vector Machine (SVM) based method for diagnosis of diabetes is proposed. In the proposed method, feature of adaptibility is added to the support vector machine. Thus, a new kind of SVM named "Adaptive SVM" is proposed, and smartly diagnosis of diseases is aimed. During the training and testing of this newly designed smart system, diabetes data set which is obtained from the medical database of University of California is used. It is observed that the classification rate of this newly proposed method on the diabetes data set is 100%.
Keywords :
"Diabetes","Support vector machines","Conferences","Diseases","Artificial neural networks","Breast cancer"
Publisher :
ieee
Conference_Titel :
Signal Processing and Communications Applications (SIU), 2011 IEEE 19th Conference on
ISSN :
2165-0608
Print_ISBN :
978-1-4577-0462-8
Type :
conf
DOI :
10.1109/SIU.2011.5929583
Filename :
5929583
Link To Document :
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