Construction of Reform Evaluation Model of Ideological and Political Education in Colleges and Universities Based on SVM
Authors
Zuguo Yin1, *
1Jiangxi University of Software Professional Technology, Nanchang, 330004, Jiangxi, China
*Corresponding author.
Email: zhc010314@163.com
Corresponding Author
Zuguo Yin
Available Online 9 December 2022.
- DOI
- 10.2991/978-94-6463-012-1_57How to use a DOI?
- Keywords
- Support Vector Machine; Evaluation Model; Multi-Classification Algorithm; Orthogonal Design
- Abstract
The evaluation model based on ideological and political education reform in SVM is essentially to optimize the level of ideological and political education reform, and to introduce the support vector machine multi-classification algorithm in the evaluation of ideological and political education reform. Through orthogonal design and output training samples, the evaluation model of ideological and political education reform in universities can be constructed. Simulation results also prove that this can effectively simplify the nonlinear classification problem and obtain more accurate evaluation results.
- 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
TY - CONF AU - Zuguo Yin PY - 2022 DA - 2022/12/09 TI - Construction of Reform Evaluation Model of Ideological and Political Education in Colleges and Universities Based on SVM BT - Proceedings of the 2022 International Conference on Educational Innovation and Multimedia Technology (EIMT 2022) PB - Atlantis Press SP - 507 EP - 514 SN - 2667-128X UR - https://doi.org/10.2991/978-94-6463-012-1_57 DO - 10.2991/978-94-6463-012-1_57 ID - Yin2022 ER -