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Automated Prediction of Employee Attrition Using Ensemble Model Based on Machine Learning Algorithms
Competent employees are a rare commodity for great companies. The problem of maintaining good employees with experience threatens the owners of companies. The issue of employee attrition can cost employers a lot as it takes a lot to compensate for their expertise and efficiency. For this reason, in...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9251085/ https://www.ncbi.nlm.nih.gov/pubmed/35795740 http://dx.doi.org/10.1155/2022/7728668 |
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author | Alsheref, Fahad Kamal Fattoh, Ibrahim Eldesouky M.Ead, Waleed |
author_facet | Alsheref, Fahad Kamal Fattoh, Ibrahim Eldesouky M.Ead, Waleed |
author_sort | Alsheref, Fahad Kamal |
collection | PubMed |
description | Competent employees are a rare commodity for great companies. The problem of maintaining good employees with experience threatens the owners of companies. The issue of employee attrition can cost employers a lot as it takes a lot to compensate for their expertise and efficiency. For this reason, in this research, we present an automated model that can predict employee attrition based on different predictive analytical techniques. These techniques have been applied with different pipeline architectures to select the best champion model. Also, an autotuning approach has been implemented to calculate the best combination of hyper parameters to build the champion model. Finally, we propose an ensemble model for selecting the most efficient model subject to different assessments measures. The results of the proposed model show that no model up until now could be considered ideal and perfect for each case of business context. Yet, our chosen model was pretty much optimal as per our requirements and adequately satisfied the intended goal. |
format | Online Article Text |
id | pubmed-9251085 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-92510852022-07-05 Automated Prediction of Employee Attrition Using Ensemble Model Based on Machine Learning Algorithms Alsheref, Fahad Kamal Fattoh, Ibrahim Eldesouky M.Ead, Waleed Comput Intell Neurosci Research Article Competent employees are a rare commodity for great companies. The problem of maintaining good employees with experience threatens the owners of companies. The issue of employee attrition can cost employers a lot as it takes a lot to compensate for their expertise and efficiency. For this reason, in this research, we present an automated model that can predict employee attrition based on different predictive analytical techniques. These techniques have been applied with different pipeline architectures to select the best champion model. Also, an autotuning approach has been implemented to calculate the best combination of hyper parameters to build the champion model. Finally, we propose an ensemble model for selecting the most efficient model subject to different assessments measures. The results of the proposed model show that no model up until now could be considered ideal and perfect for each case of business context. Yet, our chosen model was pretty much optimal as per our requirements and adequately satisfied the intended goal. Hindawi 2022-06-26 /pmc/articles/PMC9251085/ /pubmed/35795740 http://dx.doi.org/10.1155/2022/7728668 Text en Copyright © 2022 Fahad Kamal Alsheref et al. https://creativecommons.org/licenses/by/4.0/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. |
spellingShingle | Research Article Alsheref, Fahad Kamal Fattoh, Ibrahim Eldesouky M.Ead, Waleed Automated Prediction of Employee Attrition Using Ensemble Model Based on Machine Learning Algorithms |
title | Automated Prediction of Employee Attrition Using Ensemble Model Based on Machine Learning Algorithms |
title_full | Automated Prediction of Employee Attrition Using Ensemble Model Based on Machine Learning Algorithms |
title_fullStr | Automated Prediction of Employee Attrition Using Ensemble Model Based on Machine Learning Algorithms |
title_full_unstemmed | Automated Prediction of Employee Attrition Using Ensemble Model Based on Machine Learning Algorithms |
title_short | Automated Prediction of Employee Attrition Using Ensemble Model Based on Machine Learning Algorithms |
title_sort | automated prediction of employee attrition using ensemble model based on machine learning algorithms |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9251085/ https://www.ncbi.nlm.nih.gov/pubmed/35795740 http://dx.doi.org/10.1155/2022/7728668 |
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