Mô hình tối ưu cho bài toán dự đoán kết quả học tập của sinh viên Trường Đại học Đồng Tháp

Abstract

This article applies the Naive Bayesian classifier, decision tree and neural nets, to set up, evaluate and come up with an optimal model, based on database at Dong Thap University. It recommends that the Naïve Bayesian is the optimal model for predicting students’ learning results at Dong Thap University. Thereby, it helps students to set learning objectives and make plans for their entire traning programs and each semester, as such to obtain results as expected.