Student Performance Prediction using various machine learning algorithms
Abstract
Student Performance Analysis System is a new discipline that is critical to helping students and professors at colleges and institutions.
The majority of available approaches are solely dependent on students' previous academic success.
This research seeks to create models that can predict a student's performance and grades while taking into account other equally important personality traits such as age, parental status, and other lifestyle factors.
To forecast student performance, it employs a variety of machine learning methods such as KNN, Naive Bayes, and Random Forest, as well as basic exploratory data analysis.