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Application of data mining technology in college mental health education
In order to improve education and teaching methods and meet the “heart” needs of college students in the era of big data, this paper analyzes the application of data mining technology in college mental health education, and introduces database technology and decision tree algorithm to support colleg...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9403985/ https://www.ncbi.nlm.nih.gov/pubmed/36032997 http://dx.doi.org/10.3389/fpsyg.2022.974576 |
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author | Sun, Xiaocong |
author_facet | Sun, Xiaocong |
author_sort | Sun, Xiaocong |
collection | PubMed |
description | In order to improve education and teaching methods and meet the “heart” needs of college students in the era of big data, this paper analyzes the application of data mining technology in college mental health education, and introduces database technology and decision tree algorithm to support college mental health work. This process verifies the feasibility of this kind of system with the help of an example. Using the test standards outlined in this document, 1.5 previous test tasks were completed within the timeframe. During the system test, the error rate was 14% and the number of tests was 7%.However, the error rate in the development stage is 11%, which is lower than 19% of the old version. The error rate in the acceptance stage is 14%, which is lower than 5% of the old version. That is to say, most of the errors were found in time in the system analysis and design stage. 14% of the problems found in the development stage are basically small problems in the interface display, which do not need major changes. However, the old version also includes design defects found in the development stage, and only large-scale rewriting of the involved modules. In the research process, the work of mental health in Colleges and universities has been promoted. At this time, the law of psychological changes of college students has been summarized. Therefore, the support of data mining technology can better meet the needs of mental health education in Colleges and universities. |
format | Online Article Text |
id | pubmed-9403985 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94039852022-08-26 Application of data mining technology in college mental health education Sun, Xiaocong Front Psychol Psychology In order to improve education and teaching methods and meet the “heart” needs of college students in the era of big data, this paper analyzes the application of data mining technology in college mental health education, and introduces database technology and decision tree algorithm to support college mental health work. This process verifies the feasibility of this kind of system with the help of an example. Using the test standards outlined in this document, 1.5 previous test tasks were completed within the timeframe. During the system test, the error rate was 14% and the number of tests was 7%.However, the error rate in the development stage is 11%, which is lower than 19% of the old version. The error rate in the acceptance stage is 14%, which is lower than 5% of the old version. That is to say, most of the errors were found in time in the system analysis and design stage. 14% of the problems found in the development stage are basically small problems in the interface display, which do not need major changes. However, the old version also includes design defects found in the development stage, and only large-scale rewriting of the involved modules. In the research process, the work of mental health in Colleges and universities has been promoted. At this time, the law of psychological changes of college students has been summarized. Therefore, the support of data mining technology can better meet the needs of mental health education in Colleges and universities. Frontiers Media S.A. 2022-08-11 /pmc/articles/PMC9403985/ /pubmed/36032997 http://dx.doi.org/10.3389/fpsyg.2022.974576 Text en Copyright © 2022 Sun. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychology Sun, Xiaocong Application of data mining technology in college mental health education |
title | Application of data mining technology in college mental health education |
title_full | Application of data mining technology in college mental health education |
title_fullStr | Application of data mining technology in college mental health education |
title_full_unstemmed | Application of data mining technology in college mental health education |
title_short | Application of data mining technology in college mental health education |
title_sort | application of data mining technology in college mental health education |
topic | Psychology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9403985/ https://www.ncbi.nlm.nih.gov/pubmed/36032997 http://dx.doi.org/10.3389/fpsyg.2022.974576 |
work_keys_str_mv | AT sunxiaocong applicationofdataminingtechnologyincollegementalhealtheducation |