Abstract—In this study, handling with the success of pre-processing on classification tasks, artificial bee colony (ABC) algorithm is used as a pre-processor in order to improve accuracy of the support vector machine (SVM) classifier. Proposed approach is examined on three different online available dataset by using k-fold cross validation method. The results obtained are compared with the results of the classification of the datasets with pure SVM classifier. The increase of the classification accuracy is observed. By altering parameters of the suggested approach, it is thought the approach would be more successful on the different datasets.

Index Terms—Artificial bee colony, support vector machine, medical data classification.

The authors are with the Department of Computer Engineering, Selçuk University, Konya, Turkey (e-mail: ababalik@selcuk.edu.tr).


Cite: Ahmet Babalık, İsmail Babaoğlu, and Ahmet Özkış, "A Pre-Processing Approach Based on Artificial Bee Colony for Classification by Support Vector Machine," International Journal of Computer and Communication Engineering vol. 2, no. 1, pp. 68-70, 2013.