Empirical Analysis of Student Performance Using Data Mining Approaches
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.