A NOVEL EFFICIENT MODEL FOR PREDICTING STUDENTS PERFORMANCE USING CLASSIFICATION METHOD

Authors

  • Deepika D Patil Computer Science and Engineering , GITCET
  • Ramesh Medar Computer Science and Engineering, GITCET

Keywords:

Data Mining, Classification, Decision tree, Knowledge Discovery in database (KDD), ID3 Algorithm

Abstract

Student performance in university courses is of great concern to the higher education where several factors may
affect the performance. Currently the huge amount of data is stored in educational database these database contains the
useful information for predicting student performance. In this paper , the classification rule generation process is based on
the decision tree as a classification method where the generated rules are studied and evaluated. A system that facilitates the
use of the generated rules is built which allows students to predict the final grade in a course under study.

Downloads

Published

2014-12-25

How to Cite

Deepika D Patil, & Ramesh Medar. (2014). A NOVEL EFFICIENT MODEL FOR PREDICTING STUDENTS PERFORMANCE USING CLASSIFICATION METHOD. International Journal of Advance Engineering and Research Development (IJAERD), 2(2), 339–342. Retrieved from https://ijaerd.org/index.php/IJAERD/article/view/574

Issue

Vol. 2 No. 2 (2015): Volume 2 Issue 2, February 2015

Section

Articles