<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>With the popularisation of education, the number of college students is increasing day by day, and there are also more students with psychological health problems. Whether students’ psychological abnormalities can be detected in time is one of the main problems faced by colleges and universities at present. Adopting digital technology to mine, collect and analyse the data generated by psychological health education in colleges can effectively solve the dynamic development of students’ psychological health problems. Therefore, in this paper, the psychological health problems of college students are identified and classified by establishing an improved logistic regression model. The behaviour characteristics are quantified and the differences are combined according to students’ relationships with their classmates, life rules and economic conditions. The test results show that the regression effect of the model is excellent, which can identify college students’ psychological health problems and improve the intervention and treatment of educators on students’ psychological problems.</p>
</abstract>

With the popularisation of education, the number of college students is increasing day by day, and there are also more students with psychological health problems. Whether students’ psychological abnormalities can be detected in time is one of the main problems faced by colleges and universities at present. Adopting digital technology to mine, collect and analyse the data generated by psychological health education in colleges can effectively solve the dynamic development of students’ psychological health problems. Therefore, in this paper, the psychological health problems of college students are identified and classified by establishing an improved logistic regression model. The behaviour characteristics are quantified and the differences are combined according to students’ relationships with their classmates, life rules and economic conditions. The test results show that the regression effect of the model is excellent, which can identify college students’ psychological health problems and improve the intervention and treatment of educators on students’ psychological problems.

Research on identifying psychological health problems of college students by logistic regression model based on data mining

Gannan University of Science and Technology

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

With the popularisation of education, the number of college students is increasing day by day, and there are also more students with psychological health...

Research on identifying psychological health problems of college students by logistic regression model based on data mining

Online veröffentlicht: 20. Mai 2022

Seitenbereich: 2253 - 2262

Eingereicht: 14. März 2022

Akzeptiert: 10. Apr. 2022

DOI: https://doi.org/10.2478/amns.2021.2.00195

Schlüsselwörter
logistic regression model, psychological health problems, data mining

© 2023 Qian Chen, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

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Research on identifying psychological health problems of college students by logistic regression model based on data mining

Online veröffentlicht: 20. Mai 2022

Seitenbereich: 2253 - 2262

Eingereicht: 14. März 2022

Akzeptiert: 10. Apr. 2022

DOI: https://doi.org/10.2478/amns.2021.2.00195

Schlüsselwörterlogistic regression model, psychological health problems, data mining

© 2023 Qian Chen, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Schlüsselwörter
logistic regression model, psychological health problems, data mining