Support vector machines for predicting the admission decision of a candidate to the School of Physical Education and Sports at Cukurova University

The School of Physical Education and Sports at Cukurova University, Adana, Turkey conducts physical ability test to select students for admission to the School. A candidate’s performance in the physical ability test as well as his scores in the National Selection and Placement Examination and graduation grade point average (GPA) at high school are the main factors (along with some other criteria) that determine whether he will be admitted or not. In this paper, we use support vector machines (SVM) to predict in advance whether or not a candidate will be admitted to the School once he knows (or somehow has) his scores from the physical ability test. Experiments have been conducted on two different datasets, which are actual test results of candidates who applied to the School in 2006 and 2007, respectively. Results are presented also for the case when the 2006 dataset is used for training and the 2007 dataset is used for testing. The results (classification accuracies of 97.17% and 90.51% in 2006 and 2007, respectively) show that SVM-based classification is a promising tool for this application domain.