Abstract
Students’ mental health evaluation is an important part of mental health research. In recent 10 years, domestic colleges and universities have conducted a lot of research on students’ mental health evaluation, but there is generally no mature model from theory to practice. In order to solve the problems of high error rate and low efficiency in mental health evaluation, an intelligent mental health evaluation system based on decision tree algorithm is proposed. This paper first analyzes the research status of mental health intelligent evaluation, constructs a mental health intelligent evaluation system, and then uses decision tree algorithm to collect mental health intelligent evaluation data. Analyze and classify the mental health intelligence evaluation data, get the mental health intelligence analysis results, and finally analyze the feasibility and benefits of the mental health intelligence evaluation system through specific simulation experiments. The results show that the system can overcome the shortcomings of the existing mental health evaluation system, improve the accuracy of mental health evaluation, improve the effectiveness and stability of mental health evaluation, and meet the actual needs of modern mental health.
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Heilongjiang Province Philosophy and Social Science research planning project (Grant No. 21EDB078).
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© 2023 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Qi, J., Cai, Z. (2023). Research on Intelligent Evaluation of College Students’ Mental Health Based on Decision Tree Algorithm. In: Jan, M.A., Khan, F. (eds) Application of Big Data, Blockchain, and Internet of Things for Education Informatization. BigIoT-EDU 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 467. Springer, Cham. https://doi.org/10.1007/978-3-031-23944-1_11
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