Feature Selection Method Based on Artificial Bee Colony Algorithm and Support Vector Machines for Medical Datasets Classification
Joint Authors
Uzer, Mustafa Serter
Yilmaz, Nihat
Inan, Onur
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-07-28
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
This paper offers a hybrid approach that uses the artificial bee colony (ABC) algorithm for feature selection and support vector machines for classification.
The purpose of this paper is to test the effect of elimination of the unimportant and obsolete features of the datasets on the success of the classification, using the SVM classifier.
The developed approach conventionally used in liver diseases and diabetes diagnostics, which are commonly observed and reduce the quality of life, is developed.
For the diagnosis of these diseases, hepatitis, liver disorders and diabetes datasets from the UCI database were used, and the proposed system reached a classification accuracies of 94.92%, 74.81%, and 79.29%, respectively.
For these datasets, the classification accuracies were obtained by the help of the 10-fold cross-validation method.
The results show that the performance of the method is highly successful compared to other results attained and seems very promising for pattern recognition applications.
American Psychological Association (APA)
Uzer, Mustafa Serter& Yilmaz, Nihat& Inan, Onur. 2013. Feature Selection Method Based on Artificial Bee Colony Algorithm and Support Vector Machines for Medical Datasets Classification. The Scientific World Journal،Vol. 2013, no. 2013, pp.1-10.
https://search.emarefa.net/detail/BIM-1012238
Modern Language Association (MLA)
Uzer, Mustafa Serter…[et al.]. Feature Selection Method Based on Artificial Bee Colony Algorithm and Support Vector Machines for Medical Datasets Classification. The Scientific World Journal No. 2013 (2013), pp.1-10.
https://search.emarefa.net/detail/BIM-1012238
American Medical Association (AMA)
Uzer, Mustafa Serter& Yilmaz, Nihat& Inan, Onur. Feature Selection Method Based on Artificial Bee Colony Algorithm and Support Vector Machines for Medical Datasets Classification. The Scientific World Journal. 2013. Vol. 2013, no. 2013, pp.1-10.
https://search.emarefa.net/detail/BIM-1012238
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1012238