Current - Issue

1. P. Cortez and A. Silva, “Using Data Mining to Predict Secondary School Student Performance,” in Proceedings of 5th Future Business
Technology Conference, 2008.
2. S. B. Kotsiantis, C. J. Pierrs, and P. E. Pintelas, “Predicting Students’ Performance in Distance Learning Using Machine Learning
Techniques,” Applied Artificial Intelligence, vol. 18, no. 5, pp. 411–426, 2010.
3. U. K. Pandey and S. Pal, “Data Mining: A Prediction of Performer or Underperformer Using Classification,” International Journal of
Computer Science and Information Security, vol. 9, no. 4, pp. 136–140, 2011.
4. S. Huang and N. Fang, “Predicting Student Academic Performance in an Engineering Dynamics Course: A Comparison of Four Types of
Predictive Mathematical Models,” Computers & Education, vol. 61, pp. 133–145, 2013.
5. F. Ahmad, N. H. Ismail, and A. A. Aziz, “The Prediction of Students’ Academic Performance Using Classification Data Mining
Techniques,” Applied Mathematical Sciences, vol. 9, no. 129, pp. 6415– 6426, 2015.
6. C.Romero and S. Ventura, “Educational Data Mining: A Review of the State of the Art,” IEEE Transactions on Systems,ogolo Man, and
Cybernetics, vol. 40, no. 6, pp. 601–618, 2010.
7. T. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning, 2nd ed., Springer, 2009.
8. I. Goodfellow, Y. Bengio, and A. Courville, Deep Learning, MIT Press, 2016.
9. D. P. Kingma and J. Ba, “Adam: A Method for Stochastic Optimization,” arXiv preprint arXiv: 1412.6980, 2014.
10. S. Kotsiantis, “Use of Machine Learning Techniques for Educational Proposes: A Decision Support System for Forecasting Students’
Grades,” Artificial Intelligence Review, vol. 37, no. 4, pp. 331–344, 2012.