STUDENT PERFORMANCE PREDICTION SYSTEM USING DATA MINING CLASSIFICATION AND CLUSTERING

Computer Engineering

The System aims towards prediction of academic performance of students for academic year on the basis of different parameters related to previous year on the basis of different parameters related to previous year using data mining classification and clustering. An educational institution needs to have an approximate prior knowledge of enrolled students to predict their performance in future academics. This helps them to identify promising students and also provides them an opportunity to pay attention to and improve those who would probably get lower grades. As a solution, we will develop a system which can predict the performance of students from their previous performances using concepts of data mining techniques under classification and clustering. By applying the K-Means and its improved K-Means, CART (Classification and Regression Tree) and its improved R2-CART Algorithm on this data, we have predicted the general and individual performance of freshly admitted students in future examinations.

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