Analysis of Student Academic Performance using Regression Methods
S. Kranthi Reddy1, S. Poojitha2, G. Bhargavi3, B. Harika4
1S. Kranthi Reddy, Assistant Professor, Department of CSE, Vignan Institute of Technology and Science, Hyderabad, India.
2S. Poojitha, B.Tech (CSE), Vignan Institute of Technology and Science, Hyderabad, India.
3G. Bhargavi, B.Tech (CSE), Vignan Institute of Technology and Science, Hyderabad, India.
4B. Harika, B.Tech (CSE), Vignan Institute of Technology and Science, Hyderabad, India.
Manuscript received on March 01, 2019. | Revised Manuscript Received on March 22, 2019. | Manuscript published on March 20, 2019. | PP: 15-18 | Volume-5 Issue-3, March 2019. | Retrieval Number: C0892035319/19©BEIESP
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© The Authors. Published By: 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: In the educational industry, student’s early performance prediction is important so that strategic intervention can be planned before students reach the final semester. With rapid change in the technology and the lot innovative software, it has become quite convenient to analyze the performance of the student. Machine Learning plays an important role in today’s world and it helps the educational institutions to predict and make decisions related to student’s performance. The scope of this paper is to predict the student marks through desktop application. In this project, the data of our institute students is taken and regression algorithms are applied to predict the academic status of the student.
Keywords: Desktop application, Machine Learning, Regression algorithms, Student’s performance