Empirical Analysis of Student Performance Using Data Mining Approaches

  • Dr. Amala Nirmal Doss, Ratchana Rajendran, Muthukumar Subramanian,Dr. Jnaneshwar Pai Maroor, Md. Khaja Mohiddin

Abstract

This paper offers a method for student results for data mining. In order to improve the performance of high school students, special methods such as expanded cluster analysis and regression trees and variable selection are used earlier on the analysis and study of individual characteristics. In the next point, numerous additional, predictable, ways to life-specific prediction models were created, while recognition criteria were discovered that account for educational attainment in the following examinations. with the approach thus used captures an accurate representation of the current assessments, since findings were based on authentic documents.

Published
2021-05-17
How to Cite
Dr. Amala Nirmal Doss, Ratchana Rajendran, Muthukumar Subramanian,Dr. Jnaneshwar Pai Maroor, Md. Khaja Mohiddin. (2021). Empirical Analysis of Student Performance Using Data Mining Approaches. Design Engineering, 737 - 748. Retrieved from http://www.thedesignengineering.com/index.php/DE/article/view/1587
Section
Articles