STUDENT PERFORMANCE PREDICTOR USING RANDOM FOREST

Project Algorithm :

Random Forest, a supervised machine learning algorithm

Project Overview :

Academic performance prediction is essential for early intervention and student support. Traditional evaluation methods only assess outcomes after exams, which limits proactive academic guidance. This project proposes a Student Performance Prediction System using Random Forest, a supervised machine learning algorithm, to predict a student’s performance based on multiple factors such as demographics, study time, health, attendance, previous grades, parental education, and internet access. This model helps educators identify at-risk students and improve academic outcomes through data-driven insights.

Reference Video : -