Association Rule Mining of Classified Data for Predicting Courses Selected by Students in E-Learning

Abstract - Data mining is the process which discovers new pattern in large database. Classification & association rule are the techniques of data mining. Classification is supervised machine learning technique which predicts the group membership for data instances. The ADTree (Alternating Decision Tree) is a classification technique that combines decision trees with the predictive accuracy into a set of classification rules. Association rule algorithms are used to show the relationship between data items. Here in this paper we combine these two algorithms & apply it to data obtained from Moodle courses of our college for the Course Recommender System which predicts the course selected by the students. First we apply only association rule to the data & then we consider this combined approach. Here we present the advantage of applying the combined approach to Course Recommender System as compare to the result of application of only the association rule algorithm.