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Analysis of the Impact of Selected Physical Environmental Factors on the Health of Employees: Creating a Classification Model Using a Decision Tree

During the process of designing and implementing a working environment, there is a need to guarantee adequate conditions for future workers’ health and well-being. This article addresses the classification of employees characterized by several basic input variables (gender, age, class of work). The...

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Detalles Bibliográficos
Autores principales: Andrejiová, Miriam, Piňosová, Miriama, Králiková, Ružena, Dolník, Bystrík, Liptai, Pavol, Dolníková, Erika
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6950521/
https://www.ncbi.nlm.nih.gov/pubmed/31842434
http://dx.doi.org/10.3390/ijerph16245080
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author Andrejiová, Miriam
Piňosová, Miriama
Králiková, Ružena
Dolník, Bystrík
Liptai, Pavol
Dolníková, Erika
author_facet Andrejiová, Miriam
Piňosová, Miriama
Králiková, Ružena
Dolník, Bystrík
Liptai, Pavol
Dolníková, Erika
author_sort Andrejiová, Miriam
collection PubMed
description During the process of designing and implementing a working environment, there is a need to guarantee adequate conditions for future workers’ health and well-being. This article addresses the classification of employees characterized by several basic input variables (gender, age, class of work). The investigated variable was the health of employees. This article aims to create a prediction classification model using the classification tree, which can be used to classify new cases into appropriate classes as accurately as possible. Objective measurements of microclimatic parameters were performed by the Testo 435 instrument. The subjective evaluation was performed by a questionnaire survey formed from the training group of 80 respondents and independently verified by the test group of 80 more respondents. The result confusion matrix shows that the number of correctly classified respondents was 69 from a total of 80 respondents. The overall accuracy was [Formula: see text] , which means that the likelihood that respondents are properly classified in the correct health class is 86.3%. Based on the model obtained using the classification tree, we can classify respondents into the relevant class for their state of health. The respondent is classified into the class of work for which particular health and working conditions are most likely.
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spelling pubmed-69505212020-01-16 Analysis of the Impact of Selected Physical Environmental Factors on the Health of Employees: Creating a Classification Model Using a Decision Tree Andrejiová, Miriam Piňosová, Miriama Králiková, Ružena Dolník, Bystrík Liptai, Pavol Dolníková, Erika Int J Environ Res Public Health Article During the process of designing and implementing a working environment, there is a need to guarantee adequate conditions for future workers’ health and well-being. This article addresses the classification of employees characterized by several basic input variables (gender, age, class of work). The investigated variable was the health of employees. This article aims to create a prediction classification model using the classification tree, which can be used to classify new cases into appropriate classes as accurately as possible. Objective measurements of microclimatic parameters were performed by the Testo 435 instrument. The subjective evaluation was performed by a questionnaire survey formed from the training group of 80 respondents and independently verified by the test group of 80 more respondents. The result confusion matrix shows that the number of correctly classified respondents was 69 from a total of 80 respondents. The overall accuracy was [Formula: see text] , which means that the likelihood that respondents are properly classified in the correct health class is 86.3%. Based on the model obtained using the classification tree, we can classify respondents into the relevant class for their state of health. The respondent is classified into the class of work for which particular health and working conditions are most likely. MDPI 2019-12-12 2019-12 /pmc/articles/PMC6950521/ /pubmed/31842434 http://dx.doi.org/10.3390/ijerph16245080 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Andrejiová, Miriam
Piňosová, Miriama
Králiková, Ružena
Dolník, Bystrík
Liptai, Pavol
Dolníková, Erika
Analysis of the Impact of Selected Physical Environmental Factors on the Health of Employees: Creating a Classification Model Using a Decision Tree
title Analysis of the Impact of Selected Physical Environmental Factors on the Health of Employees: Creating a Classification Model Using a Decision Tree
title_full Analysis of the Impact of Selected Physical Environmental Factors on the Health of Employees: Creating a Classification Model Using a Decision Tree
title_fullStr Analysis of the Impact of Selected Physical Environmental Factors on the Health of Employees: Creating a Classification Model Using a Decision Tree
title_full_unstemmed Analysis of the Impact of Selected Physical Environmental Factors on the Health of Employees: Creating a Classification Model Using a Decision Tree
title_short Analysis of the Impact of Selected Physical Environmental Factors on the Health of Employees: Creating a Classification Model Using a Decision Tree
title_sort analysis of the impact of selected physical environmental factors on the health of employees: creating a classification model using a decision tree
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6950521/
https://www.ncbi.nlm.nih.gov/pubmed/31842434
http://dx.doi.org/10.3390/ijerph16245080
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