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Machine Learning for Student Performance Prediction by Prasad Athalye is a document available to read on EtoBox.

What is Machine Learning for Student Performance Prediction about?

This paper discusses the use of machine learning techniques to predict student performance, highlighting the importance of early identification of struggling students. It details a methodology involving data preprocessing, feature selection, and the evaluation of four classification models, with Support Vector Machine (SVM) achieving the highest accuracy. The findings suggest that machine learning can enhance academic planning and support targeted interventions to improve educational outcomes.

Author

Prasad Athalye

Language

EN