Classification based data mining algorithms to predict slow, average and fast learners in educational system using WEKA

Education Data Mining plays an important role on predicting student's academic performance. This paper focuses on identifying slow, average and fast learners among students and displaying it by predictive data mining model using classification based algorithms. Student Details have been referred from Sardar Patel Institute of Technology College MCA Department and prediction of learners is done by applying Naïve Bayes, J48, ZeroR and Random Tree using WEKA as an Open Source Tool. Further a comparison is made among these four classifiers to predict the accuracy and find the best performing classification among all.