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Published in:   Vol. 6 Issue 1 Date of Publication:   June 2017

A Survey on the Result Based Analysis of Student Performance using Data Mining Techniques

K. Govindasamy,T.Velmurugan

Page(s):   18-22 ISSN:   2278-2397
DOI:   10.20894/IJDMTA.102.006.001.006 Publisher:   Integrated Intelligent Research (IIR)

Extraction of information available in various data base repositories is a tedious task. A composed works of Data Mining (DM) method is accessible for different category of applications for the same work. Many researchers involve analyzing the students performance using some relevant DM techniques. This attracting little field is named as Learning Data Mining (LDM). The organizations of the syllabus also increase a very big contact about the growth of the students information and their performance. Among the different data mining methods, classification plays a vital role in learning data mining. The primary intention of this research work is to cross the data mining methods which are apply for the improvement of the students performance and also identify the most excellent appropriate structure of syllabus for the new environment. This study investigates about the use of ID3 and C4.5 classification algorithms for the improvement of student performance evaluation system. A comparative analysis of various works is carried out in this survey to identify the best classification algorithms for LDM.