A Comprehensive Analysis: Classification Techniques for Educational Data mining

Data mining is a popular trend these days, and it's being applied in a variety of fields, including student education and learning analytics. Educational Data-Mining (EDM) is a recent field of research that employs data mining (DM) techniques. It uses machine learning (ML) algorithms as well as statistical methodologies to assist the user in deciphering a student's learning habits, success in academics, and, if necessary, further progress. Manually analyzing data and uncovering hidden information is difficult and time-consuming. Classification will be employed in the article to improve educational data mining. We need to improve performance as well as the clarity of the models we acquire. In this study, we will cover various data mining strategies that can be used to forecast student performance levels.