• 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