Design of Machine Learning Based Model to Predict Students Academic Performance

Abstract

Artificial intelligence relies heavily on machine learning. Classifying and forecasting outcomes may be done using machine learning. Student performance assessment demonstrates how much effort educational institutions should put in to help the underachieving or average student. Using EDM models is important because they use previous student data to predict future student performance. To help students and teachers improve their performance, educational institutions use a range of ways to gather information on the characteristics of students who are actively engaged in the learning process. Students' performance may be predicted using this machine learning-based system. Support vector machine, ID3, and Regression Analysis are the three machine learning methods used in the model. The results of the experiments have shown that SVM's performance is concerned with the performance of the students.