Proceedings of the 2023 2nd International Conference on Educational Innovation and Multimedia Technology (EIMT 2023)

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Student Grade Prediction Model Based on RFE_RF and Integrated Learning Voting Algorithm

Authors
Yajing Niu1, Tao Zhou1, *, Zhigang Li1, Haochen Liu1
1College of Information Science and Technology, Shihezi University, Shihezi, 832000, China
*Corresponding author. Email: zt_inf@shzu.edu.cn
Corresponding Author
Tao Zhou
Available Online 4 July 2023.
DOI
10.2991/978-94-6463-192-0_154How to use a DOI?
Keywords
Feature selection; information entropy; voting algorithm; student grade prediction
Abstract

As an important branch of educational big data, grade prediction has become a hot spot for researchers. In order to predict students’ grade levels more accurately and have good prediction accuracy at each grade level, the RFE _ RF feature selection method is proposed to reduce the dimension of features. Several machine learning models, such as the decision tree, random forest, logistic regression, and Naive Bayes, are used to construct a weighted voting model based on information entropy to build a student grade prediction model with an accuracy rate of 84.38%. Compared with the performance of other single models, the accuracy, F1-score and recall rate of this model are all good at low, middle, and high-grade levels. The results show that the algorithm can provide a reference for the study of grade-influencing factors and student grade prediction model.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2023 2nd International Conference on Educational Innovation and Multimedia Technology (EIMT 2023)
Series
Atlantis Highlights in Social Sciences, Education and Humanities
Publication Date
4 July 2023
ISBN
978-94-6463-192-0
ISSN
2667-128X
DOI
10.2991/978-94-6463-192-0_154How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Yajing Niu
AU  - Tao Zhou
AU  - Zhigang Li
AU  - Haochen Liu
PY  - 2023
DA  - 2023/07/04
TI  - Student Grade Prediction Model Based on RFE_RF and Integrated Learning Voting Algorithm
BT  - Proceedings of the 2023 2nd International Conference on Educational Innovation and Multimedia Technology (EIMT 2023)
PB  - Atlantis Press
SP  - 1193
EP  - 1201
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-94-6463-192-0_154
DO  - 10.2991/978-94-6463-192-0_154
ID  - Niu2023
ER  -