The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Metadata Harvesting (OAI2)
  • Digital Archiving Policy

IJACSA

  • About the Journal
  • Call for Papers
  • Author Guidelines
  • Fees/ APC
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Editors
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Call for Papers
  • Proposals
  • Guest Editors

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future of Information and Communication Conference (FICC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Guidelines
  • Fees
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Editors
  • Reviewers
  • Subscribe

Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Machine Learning Model through Ensemble Bagged Trees in Predictive Analysis of University Teaching Performance

Author 1: Omar Chamorro-Atalaya
Author 2: Carlos Chávez-Herrera
Author 3: Marco Anton-De los Santos
Author 4: Juan Anton-De los Santos
Author 5: Almintor Torres-Quiroz
Author 6: Antenor Leva-Apaza
Author 7: Abel Tasayco-Jala
Author 8: Gutember Peralta-Eugenio

Download PDF

Digital Object Identifier (DOI) : 10.14569/IJACSA.2021.0121249

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 12, 2021.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: The objective of this study is to analyze and discuss the metrics of the Machine Learning model through the Ensemble Bagged Trees algorithm, which will be applied to data on satisfaction with teaching performance in the virtual environment. Initially the classification analysis through the Matlab R2021a software, identified an Accuracy of 81.3%, for the Ensemble Bagged Trees algorithm. When performing the validation of the collected data, and proceeding with the obtaining of the predictive model, for the 4 classes (satisfaction levels), total precision values of 82.21%, Sensitivity of 73.40%, Specificity of 91.02% and of 90.63% Accuracy. In turn, the highest level of the area under the curve (AUC) by means of the Receiver operating characteristic (ROC) is 0.93, thus considering a sensitivity of the predictive model of 93%. The validation of these results will allow the directors of the higher institution to have a database, to be used in the process of improving the quality of the educational service in relation to teaching performance.

Keywords: Machine learning; ensemble; bagged trees; predictive analysis; teaching performance

Omar Chamorro-Atalaya, Carlos Chávez-Herrera, Marco Anton-De los Santos, Juan Anton-De los Santos, Almintor Torres-Quiroz, Antenor Leva-Apaza, Abel Tasayco-Jala and Gutember Peralta-Eugenio, “Machine Learning Model through Ensemble Bagged Trees in Predictive Analysis of University Teaching Performance” International Journal of Advanced Computer Science and Applications(IJACSA), 12(12), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0121249

@article{Chamorro-Atalaya2021,
title = {Machine Learning Model through Ensemble Bagged Trees in Predictive Analysis of University Teaching Performance},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0121249},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0121249},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {12},
author = {Omar Chamorro-Atalaya and Carlos Chávez-Herrera and Marco Anton-De los Santos and Juan Anton-De los Santos and Almintor Torres-Quiroz and Antenor Leva-Apaza and Abel Tasayco-Jala and Gutember Peralta-Eugenio}
}


IJACSA

Upcoming Conferences

Future of Information and Communication Conference (FICC) 2023

2-3 March 2023

  • Hybrid | San Francisco

Computing Conference 2023

13-14 July 2023

  • Hybrid | London, UK

IntelliSys 2022

1-2 September 2022

  • Hybrid / Amsterdam

Future Technologies Conference (FTC) 2022

20-21 October 2022

  • Hybrid / Vancouver
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. Registered in England and Wales. Company Number 8933205. All rights reserved. thesai.org