Accuracy comparison of predictive algorithms of data mining: Application in education sector

Abstract

Prediction is growing area of research which is attracting many researchers. Prediction is applied to almost all the sectors. Much commercial Business Intelligence software is available in which prediction is one of the features. With the advent of Open Source Technologies, it has become possible for education sector which normally has low IT budget, to take maximum advantage of Information and Communication Technologies(ICT). This paper describes the use of Open source Software Knime for prediction of students result based upon various independent(predictor) variables and value of dependent variable can be predicted using decision tree , SOTA (Self Organizing Tree Algorithm) and Naive Bayes This paper compares these three predictive algorithms present in Knime in terms of accuracy. Predicted results are compared with the actual result in order to measure accuracy and recommends best Predictive algorithm for forecasting. This paper also demonstrates the use of Moodle - Open Source Learning Management System (LMS) Logs as one of the attributes in predicting the student results. © 2011 Springer-Verlag Berlin Heidelberg.