Admission Chance Prediction Models For The School Of Physical Education And Sports Candidates

Abstract

Admission chance prediction helps in many ways for candidates such as estimation of results, saving time and effort for higher acceptance chance, selecting the right school and making a good training plan. Admission chance prediction is also very valuable to prepare a good training plan since the physical ability test is one of the most important criteria for admission. Among many Machine Learning approaches, we only used Support Vector Machine (SVM), Single Decision Tree (SDT). In this study, these approaches were applied to train models on the dataset of 403 candidates who applied in 2018. These models were compared to each other for better accuracy and will be used them in the following years. The results were analyzed with K-fold cross-validation to decrease data dependency and increase reliability.