On predicting student performance using low-rank matrix factorization techniques

Engineering & Materials Science

• Factorization 100%
• Students 74%
• Set theory 12%
• Collaborative filtering 11%
• Singular value decomposition 10%
• Data mining 8%
• Machine learning 7%