Empirical Study on Classification Algorithm For Evaluation of Students Academic Performance

Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2015, Vol 17, Issue 6

Abstract

Abstract: Data mining techniques (DMT) are extensively used in educational field to find new hidden patterns from student’s data. In recent years, the greatest issues that educational institutions are facing the unstableexpansion of educational data and to utilize this information data to progress the quality of managerial decisions. Educational institutions are playing a prominent role in the public and also playing an essential role for enlargement and progress of nation. The idea is predicting the paths of students, thus identifying the student achievement. The data mining methods are very useful in predicting the educational database. Educational data mining is concerns with improving techniques for determining knowledge from data which comes from the educational database. However it has issue with accuracy of classification algorithms. To overcome this problem the higher accuracy of the classification J48 algorithm is used. This work takes consideration with the locality and the performance of the student in education in order to analyse the student achievement is high over schooling or in graduation.

Authors and Affiliations

Dr. S. Umamaheswari , K. S. Divyaa

Keywords

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  • EP ID EP117478
  • DOI -
  • Views 106
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How To Cite

Dr. S. Umamaheswari, K. S. Divyaa (2015). Empirical Study on Classification Algorithm For Evaluation of Students Academic Performance. IOSR Journals (IOSR Journal of Computer Engineering), 17(6), 67-73. https://europub.co.uk/articles/-A-117478