A Review on Data Mining and Machine Learning Methods for Student Scholarship Prediction

This review paper consists of literature survey to prediction of scholarship by using Machine Learning and Data Mining technique. Along with this it contains a small description of ML/DM which are used by the researchers. It also describes data sets as very important in ML/DM methods. Machine Learning becomes most popular in the field of IT industry. Nowadays Machine Learning and Data Mining turn as a powerful technique which applicable for various fields such as IT, Education sector and also in business sector too. The different types of ML/DM algorithms are addressed by using all this technique. The algorithms which give more accuracy results in detection of continuity of every student's scholarship such as Naïve Bayes, Decision Tree and k-NN. Finally, the proposed model will provide a list of candidates, who deserve to have a scholarship and also discussion has been made on accuracy of each techniques which was used to get a result.