The Naive Bayesian Approach in Classifying the Learner of Distance Education System

To provide high quality and individuation service of training is the core target of distance education system. With the vigorous development of distance education in recent years, the huge potential of education market and fierce competition bring new opportunities and challenges. Information collection and feedback of learner are important subjects in this field. Several methods of data mining and knowledge discovery can settle this matter. This study presents a new procedure, joining quantitative value of RFM (Recency, Frequency and Monetary) model and naive Bayesian algorithm, to classify the learners and offer more support to make decision. Moreover, the experimental results demonstrate that the algorithm is efficient and accurate.