Student Performance Prediction using various machine learning algorithms

  • Rashmi V. Varade, Dr. Blessy Thankanchan
Keywords: Exploratory Data Analysis, Classification Techniques, KNN, Naïve Bayes, Random Forest, Bayesian classifiers

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.

Published
2021-08-01
How to Cite
Dr. Blessy Thankanchan , R. V. V. (2021). Student Performance Prediction using various machine learning algorithms. Design Engineering, 5814- 5819. Retrieved from http://www.thedesignengineering.com/index.php/DE/article/view/3077
Section
Articles