| dc.creator |
Guraksin, Gur Emre |
|
| dc.creator |
Kose, Utku |
|
| dc.creator |
Deperlioglu, Omer |
|
| dc.date |
2014-12-31T22:00:00Z |
|
| dc.date.accessioned |
2020-10-06T09:49:33Z |
|
| dc.date.available |
2020-10-06T09:49:33Z |
|
| dc.identifier |
4871c024-c2a4-4e75-83df-5a2c59726f49 |
|
| dc.identifier |
https://avesis.sdu.edu.tr/publication/details/4871c024-c2a4-4e75-83df-5a2c59726f49/oai |
|
| dc.identifier.uri |
http://acikerisim.sdu.edu.tr/xmlui/handle/123456789/59139 |
|
| dc.description |
Approaches performed based on computer supported systems within the medical field gain more popularity day by day. In such systems, Artificial Intelligence techniques are often used for several disease diagnostics. Diabetes is one of these diseases. In this study, a diabetes diagnosis system based on Support Vector Machines has been proposed. Along training of SVM, Vortex Optimization Algorithm was used for determining the sigma parameter of the Gauss (RBF) kernel function, and a classification process has been done over the diabetes data set related to Pima Indians. |
|
| dc.language |
tur |
|
| dc.rights |
info:eu-repo/semantics/closedAccess |
|
| dc.title |
Diabetes Determination via Vortex Optimization Algorithm Based Support Vector Machines |
|
| dc.type |
info:eu-repo/semantics/conferenceObject |
|