Semi Supervised Prediction Model in Educational Data Mining

Educational Data Mining (EDM) is a developing research field that has driven many researchers' interests. The advancement in applying statistical and conventional measurements on the academic process has taken huge leaps in the past few years. In this paper, a robust prediction model based on the Random Forest Algorithm is provided. In this paper, a data set for graduate students in the University of California in Los Angeles was utilized to predict the admission acceptance. The model uses semi supervised learning for prediction and shows promising results with 91% accuracy. The suggested model provides a list of important features to be considered when applying for a university.