Machine Learning-Based Computational Optimization of Performance Prediction Model

Abstract

Predicting student success in advance can help educational institutions enhance their teaching quality. This research offers insight into predicting student success not only based on academic information but also on their social structure and living area. The goal of this study is to predict students' grades using machine learning based models such as Decision Tree, Linear Regressor, and Random Forest Regressor and to select the best model among these three.