International Journal of
Information and Education Technology

Editor-In-Chief: Prof. Jon-Chao Hong
Frequency: Monthly
ISSN: 2010-3689 (Online)
E-mali: editor@ijiet.org
Publisher: IACSIT Press
 

OPEN ACCESS
3.9
CiteScore

IJIET 2019 Vol.9(10): 710-714
doi: 10.18178/ijiet.2019.9.10.1291

Prediction of Teacher Enrollment for Pakistani Schools by Using SVM

Samina Kausar , Xu Huahu , Muhammad Shahid Iqbal , Xiangmeng Wang , Muhammad Yasir Shabir , Tamoor Khan

Abstract

Civilization distinguishes human being from other creatures. Civilization is adorned with education. Education uplifts not only the standard but also the historical records of nations. Teachers, students, public, government and curriculum are the main components of education. This study analyzes the number of school teachers and predicts the future annual enrollment of teachers using the SVM model (support vector machine). Time series data of 46 years (1971-2017) have been taken from the Handbook of Statistics on Pakistan Economy. Our results depict that school teachers must be further enrolled at all levels. Our method leads to good precision.

Keywords

  • Enrollment polices
  • future prediction
  • school teachers
  • and teacher enrollment
1291-E173

How to Cite

Copied

Samina Kausar, Xu Huahu, Muhammad Shahid Iqbal, Xiangmeng Wang, Muhammad Yasir Shabir, and Tamoor Khan, "Prediction of Teacher Enrollment for Pakistani Schools by Using SVM," International Journal of Information and Education Technology, vol. 9, no. 10, pp. 710-714, 2019. https://doi.org/10.18178/ijiet.2019.9.10.1291

Copyright & License

Copyright © 2019 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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