Student's Academic Performance Prediction by Using Ensemble Techniques

Abstract

Data Mining is a discipline of Machine Learning which is used to find or extract the information from the huge database of any organization by using some informative techniques. These informative techniques are then divided into different categories like clustering, classification, regression and association rule mining etc. Data Mining is widely used techniques in different fields like education, telecommunication, hospital, hospitality industry etc. As education plays a crucial role in the life of a human being therefore its proper monitoring is also very important. Thus, to predict the academic performance of any student on time and to help students improve their academic perform different researcher is working in the field and tried to develop a system which help to improve the prediction result. In this paper, different classification algorithms are used on academic dataset of the student in conjunction with different ensemble learning algorithm to improve the prediction result as compared to prediction result given by simple classification algorithm. At the end a comparison is also given which show the performance improvement by ensemble learning as compared to simple classification. The maximum improvement is shown by Multilayer perceptron algorithm and it is up to 15%.