APPLYING NAIVE BAYESIAN CLASSIFIER FOR PREDICTING PERFORMANCE OF A STUDENT USING WEKA

A.P. TRIBHUVAN¹*, P.P. TRIBHUVAN², J.G. GADE^3
1Department of Computer Science, Marathwada Institute of Technology, Aurangabad- 431 028, MS, India.
²Deogiri Institute of Engineering and Management Studies, Aurangabad- 431 005, MS, India.
³Department of Industrial Automation, J.E.S. College, Jalna - 431 203, MS, India
* Corresponding Author : amrapaliprakash512@gmail.com

Received : 18-12-2014     Accepted : 15-01-2015     Published : 23-01-2015
Volume : 7     Issue : 1       Pages : 239 - 242
Adv Comput Res 7.1 (2015):239-242

Keywords : Naive bayes, Classification, Decision Tree, Data Mining
Conflict of Interest : None declared

The advances in computing and information storage have provided vast amounts of data. The challenge has been to extract knowledge from this raw data that has guide to new methods and techniques such as data mining that can link the knowledge gap. This paper aimed to review these new data mining techniques and predicting the performance of a student is a great concern to the higher education managements, where quite a few factors affect the performance. The scope of this paper is to explore the accuracy of data mining techniques. We collected records of 100 under graduate students from a private Educational Institution conducting various Under Graduate courses of Information Technology. Decision tree and Naive bayes algorithms were evaluated by using WEKA tool to discover the performance. Decision tree algorithm is more accurate than the Naive bayes algorithm. This work will help the Educational Institution to precisely predict the performance of the students.