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Identification Method of Influencing Factors of Hospital Catering Service Satisfaction Based on Decision Tree Algorithm
Entering the 21st century, material abundance has been greatly enriched, and living standards have been continuously improved. Now society is gradually moving towards the era of experience economy. From the perspective of experience economy, patients' demands for hospitals are not only the sati...
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/PMC9050333/ https://www.ncbi.nlm.nih.gov/pubmed/35498141 http://dx.doi.org/10.1155/2022/6293908 |
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author | Li, Siyao Xu, Di Liu, Yang Wang, Rui Zhang, Jian |
author_facet | Li, Siyao Xu, Di Liu, Yang Wang, Rui Zhang, Jian |
author_sort | Li, Siyao |
collection | PubMed |
description | Entering the 21st century, material abundance has been greatly enriched, and living standards have been continuously improved. Now society is gradually moving towards the era of experience economy. From the perspective of experience economy, patients' demands for hospitals are not only the satisfaction of medical technology, but their catering consumption also has begun to change to the pursuit of higher requirements. Decision tree algorithm is a kind of data mining algorithm. Data mining technology is a young technology for data analysis. It can simulate mathematical models or algorithms through data analysis, which greatly improves the prediction accuracy. This paper aims to study how to identify the influencing factors of hospital catering service satisfaction, and proposes the application of decision tree algorithm to the hospital catering service satisfaction research, and proposes decision tree-related algorithms, such as ID3, C4.5, and C5.0. Based on the analysis of patients' satisfaction with the hospital catering service in a certain hospital, the results of the model study based on the decision tree algorithm show that the risk estimation value of the training set is 0.064, and the total correct percentage is 93.6%. The risk estimate for the test set was 0.065, for a total correct percentage of 93.5%. It can be seen that the effect of the model is good and can be effectively predicted. |
format | Online Article Text |
id | pubmed-9050333 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-90503332022-04-29 Identification Method of Influencing Factors of Hospital Catering Service Satisfaction Based on Decision Tree Algorithm Li, Siyao Xu, Di Liu, Yang Wang, Rui Zhang, Jian Appl Bionics Biomech Research Article Entering the 21st century, material abundance has been greatly enriched, and living standards have been continuously improved. Now society is gradually moving towards the era of experience economy. From the perspective of experience economy, patients' demands for hospitals are not only the satisfaction of medical technology, but their catering consumption also has begun to change to the pursuit of higher requirements. Decision tree algorithm is a kind of data mining algorithm. Data mining technology is a young technology for data analysis. It can simulate mathematical models or algorithms through data analysis, which greatly improves the prediction accuracy. This paper aims to study how to identify the influencing factors of hospital catering service satisfaction, and proposes the application of decision tree algorithm to the hospital catering service satisfaction research, and proposes decision tree-related algorithms, such as ID3, C4.5, and C5.0. Based on the analysis of patients' satisfaction with the hospital catering service in a certain hospital, the results of the model study based on the decision tree algorithm show that the risk estimation value of the training set is 0.064, and the total correct percentage is 93.6%. The risk estimate for the test set was 0.065, for a total correct percentage of 93.5%. It can be seen that the effect of the model is good and can be effectively predicted. Hindawi 2022-04-21 /pmc/articles/PMC9050333/ /pubmed/35498141 http://dx.doi.org/10.1155/2022/6293908 Text en Copyright © 2022 Siyao Li 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 Li, Siyao Xu, Di Liu, Yang Wang, Rui Zhang, Jian Identification Method of Influencing Factors of Hospital Catering Service Satisfaction Based on Decision Tree Algorithm |
title | Identification Method of Influencing Factors of Hospital Catering Service Satisfaction Based on Decision Tree Algorithm |
title_full | Identification Method of Influencing Factors of Hospital Catering Service Satisfaction Based on Decision Tree Algorithm |
title_fullStr | Identification Method of Influencing Factors of Hospital Catering Service Satisfaction Based on Decision Tree Algorithm |
title_full_unstemmed | Identification Method of Influencing Factors of Hospital Catering Service Satisfaction Based on Decision Tree Algorithm |
title_short | Identification Method of Influencing Factors of Hospital Catering Service Satisfaction Based on Decision Tree Algorithm |
title_sort | identification method of influencing factors of hospital catering service satisfaction based on decision tree algorithm |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9050333/ https://www.ncbi.nlm.nih.gov/pubmed/35498141 http://dx.doi.org/10.1155/2022/6293908 |
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