Demystifying and Anticipating Graduate School Admissions using Machine Learning Algorithms

One of the many aspirations of undergraduate students in India is going for further graduate studies. Unfortunately, many students spend months and years of preparation focusing on things that unfortunately won’t improve their chances of getting into a good graduate school. This paper evaluates the chances of applicants to get into a particular graduate program using various classification and regression approaches of Machine Learning. Various algorithms have been pitted against each other and also the most important features have been extracted which are useful to get into a graduate school program. Using unsupervised approach, this paper finds various categories of students and pool them together to find if they are perfect fit for admission or not. A novel approach of predicting the chances for admission in graduate school is introduced in this paper.