Performance Analysis of Students Using Machine Learning & Data Mining Approach
Mukesh Kumar1, A. J. Singh2
1Mukesh Kumar, Assistant Professor, Chitkara University School of Engineering and Technology, Chitkara University, Himachal Pradesh, India.
2Prof. A. J. Singh, Department of Computer Science, Himachal Pradesh University, Summer-hill, Shimla (Himachal Pradesh), India.
Manuscript received on 18 February 2019 | Revised Manuscript received on 27 February 2019 | Manuscript published on 28 February 2019 | PP: 75-79 | Volume-8 Issue-3, February 2019 | Retrieval Number: C5708028319/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Performance evaluation of students is essential to check the feasibility of improvement. Regular evaluation not only improves the performance of the student but also it helps in understanding where the student is lacking. It takes a lot of manual effort to complete the evaluation process as even one college may contain thousands of students. This paper proposed an automated solution for the performance evaluation of the students using machine learning. A threshold-based segmentation is employed to complete the evaluation procedure over MATLAB simulation tool. The performance of machine learning is evaluated by accuracy and mean square error.
Keywords: Performance Evaluation, Machine Learning, Performance Improvement, MATLAB, Mean Square Error, Estimation Effort
Scope of the Article: Machine Learning