Applying Classification Techniques in Machine Learning to Predict Job Satisfaction of University Professors: A Sociodemographic and Occupational Perspective
- DOI
- 10.3390/computers13120344
- Published
- 2024-12-17
- Container
- Computers
- Publisher
- MDPI AG
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3390/computers13120344,
title = {Applying Classification Techniques in Machine Learning to Predict Job Satisfaction of University Professors: A Sociodemographic and Occupational Perspective},
author = {Carlos Alberto Espinosa-Pinos and Paúl Bladimir Acosta-Pérez and Camila Alessandra Valarezo-Calero},
year = {2024},
journal = {Computers},
doi = {10.3390/computers13120344},
url = {https://doi.org/10.3390/computers13120344}
}RIS
TY - JOUR TI - Applying Classification Techniques in Machine Learning to Predict Job Satisfaction of University Professors: A Sociodemographic and Occupational Perspective AU - Carlos Alberto Espinosa-Pinos AU - Paúl Bladimir Acosta-Pérez AU - Camila Alessandra Valarezo-Calero PY - 2024 JO - Computers DO - 10.3390/computers13120344 UR - https://doi.org/10.3390/computers13120344 ER -
APA
Espinosa-Pinos, C. A., Acosta-Pérez, P. B., & Valarezo-Calero, C. A. (2024). Applying Classification Techniques in Machine Learning to Predict Job Satisfaction of University Professors: A Sociodemographic and Occupational Perspective. Computers. https://doi.org/10.3390/computers13120344
Source records
- crossref · retrieved 2026-09-25T21:10:52.638Z