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Analysis of Improving Effect of Running APP on College Students' Physique by Using Student Data Mining Technology

With the continuous development of sports software, college students, as the most advanced social new ideological group, running APP gradually enter the study and life of college students. Based on students' DM (data mining), this paper analyzes the influence of running apps on the improvement...

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Detalles Bibliográficos
Autor principal: Zhuo, Ni
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9334120/
https://www.ncbi.nlm.nih.gov/pubmed/35909875
http://dx.doi.org/10.1155/2022/4807953
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author Zhuo, Ni
author_facet Zhuo, Ni
author_sort Zhuo, Ni
collection PubMed
description With the continuous development of sports software, college students, as the most advanced social new ideological group, running APP gradually enter the study and life of college students. Based on students' DM (data mining), this paper analyzes the influence of running apps on the improvement of college students' physique, chooses DT (decision tree) algorithm to construct the structure according to the characteristics of the data used, obtains students' DM model, and prunes it by using substitution error rate and PEP (pessimistic error pruning). The results show that the results of intra-group comparison among boys show that the scores of 1000 m in the intervention group have no obvious change compared with those before the intervention, and the difference is not statistically significant (P=0.516). The 800 m scores of girls in the intervention group were better than those in the control group, and the difference was statistically significant (P=0.03). The results of intra-group comparison showed that there was no significant difference in the scores of the intervention group before and after the intervention, and the difference was not statistically significant (P=0.32). After the experiment, the vital capacity scores of boys and girls in APP intervention group and control group were improved, with statistical significance (P < 0.05). The conclusion shows that running APP can improve students' speed level, cultivate students' endurance level, and improve students' physical health.
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spelling pubmed-93341202022-07-29 Analysis of Improving Effect of Running APP on College Students' Physique by Using Student Data Mining Technology Zhuo, Ni Comput Intell Neurosci Research Article With the continuous development of sports software, college students, as the most advanced social new ideological group, running APP gradually enter the study and life of college students. Based on students' DM (data mining), this paper analyzes the influence of running apps on the improvement of college students' physique, chooses DT (decision tree) algorithm to construct the structure according to the characteristics of the data used, obtains students' DM model, and prunes it by using substitution error rate and PEP (pessimistic error pruning). The results show that the results of intra-group comparison among boys show that the scores of 1000 m in the intervention group have no obvious change compared with those before the intervention, and the difference is not statistically significant (P=0.516). The 800 m scores of girls in the intervention group were better than those in the control group, and the difference was statistically significant (P=0.03). The results of intra-group comparison showed that there was no significant difference in the scores of the intervention group before and after the intervention, and the difference was not statistically significant (P=0.32). After the experiment, the vital capacity scores of boys and girls in APP intervention group and control group were improved, with statistical significance (P < 0.05). The conclusion shows that running APP can improve students' speed level, cultivate students' endurance level, and improve students' physical health. Hindawi 2022-07-21 /pmc/articles/PMC9334120/ /pubmed/35909875 http://dx.doi.org/10.1155/2022/4807953 Text en Copyright © 2022 Ni Zhuo. 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
Zhuo, Ni
Analysis of Improving Effect of Running APP on College Students' Physique by Using Student Data Mining Technology
title Analysis of Improving Effect of Running APP on College Students' Physique by Using Student Data Mining Technology
title_full Analysis of Improving Effect of Running APP on College Students' Physique by Using Student Data Mining Technology
title_fullStr Analysis of Improving Effect of Running APP on College Students' Physique by Using Student Data Mining Technology
title_full_unstemmed Analysis of Improving Effect of Running APP on College Students' Physique by Using Student Data Mining Technology
title_short Analysis of Improving Effect of Running APP on College Students' Physique by Using Student Data Mining Technology
title_sort analysis of improving effect of running app on college students' physique by using student data mining technology
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9334120/
https://www.ncbi.nlm.nih.gov/pubmed/35909875
http://dx.doi.org/10.1155/2022/4807953
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