Model of Tuned J48 Classification and Analysis of Performance Prediction in Educational Data Mining

摘要

Information-Technology (IT) and Data Engineering in Education nowadays decides the quality and pace of learning achieved by. Use of Information Engineering and Machine Intelligence generate precise advantages in Optimisation problems of performances and prediction. Many Data Mining algorithms have so far proved to be serving their best in many cases. A tuned J48 is all-around considered in this paper along with the base performance evaluation and analysis of Naive Bayes, Bayes Net, Multilayer Perceptron, SVM, REPTree and Random Forest with Two Datasets given. Researches in EDM reveal that classification outperforms other mining methodologies. Hence, a comprehensive analysis of Models of Classification is also proposed in this research. Besides these, in this paper, Weka, is used for the base performance calculations. The prerogative of this research reveals that though many models are very competent, few are not; the performance of tuned J48 invites the attention, as its result provide realistic best, compared to others. It is obvious that combinational use of models or an improved and optimised method of J48 classification would be a great choice to enhance the classification accuracy and prediction of Students.