Admission Prediction for Higher Studies in Foreign Universities

In India every year lakhs of students are getting the graduation degree and willing to join post-graduation in other countries. Newly graduate students usually are not knowledgeable of the requirements, and the procedures of the postgraduate admission and might spend a considerable amount of money to get advice from consultancy organizations to help them identify their admission chances. This paper helps on predicting the eligibility of Indian students getting admission in best university based on their test attributes like GRE, TOEFL, LOR, SOP, CGPA, university rating, and research. According to their scores, the possibilities of chance of admit are calculated, but with the growth of machine learning methods, we have got the flexibility to search out an answer to the current issue. The present system focuses on the prediction whether a student’s score is appropriate or not by using algorithms such as AdaBoost, CatBoost, support vector machine, and Naive Bayes. Random forest, decision tree, and linear regression algorithms are used for predicting this model. This algorithm is trained and tested for predicting the admission for the student.