Abstract
Mental health is an important basic condition for college students to become adults. Educators gradually attach importance to strengthening the mental health education of college students. This paper makes a detailed analysis and research on college students’ mental health, expounds the development and application of clustering analysis algorithm, applies the distance formula and clustering criterion function commonly used in clustering analysis, and makes a specific description of some classic algorithms of clustering analysis. Based on expounding the advantages and disadvantages of fast-clustering analysis algorithm and hierarchical clustering analysis algorithm, this paper introduces the concept of the two-step clustering algorithm, discusses the algorithm flow of clustering model in detail, and gives the algorithm flow chart. The main work of this paper is to analyze the clustering algorithm of students’ mental health database formed by mental health assessment tool test, establish a data mining model, mine the database, analyze the state characteristics of different college students’ mental health, and provide corresponding solutions. In order to meet the needs of the psychological management system based on the clustering analysis method, the clustering analysis algorithm is used to cluster the data. Based on the original database, this paper establishes the methods of selecting, cleaning, and transforming the data of students’ psychological archives. Finally, it expounds on the application of data mining in students’ psychological management system and summarizes and prospects the implementation of the system.
Highlights
Nowadays, the world is in an era of fierce competition. e so-called competition is essentially the competition of talents
Many health care institutions in colleges and universities have done a lot of work in carrying out mental health education, psychological or counseling for college students
E fourth section establishes the mental health data model based on the clustering analysis algorithm. e fifth section is based on the mental health data mining of college students, combined with the actual clustering analysis algorithm research, and verifies the performance of the algorithm through implementation. e sixth section summarizes the core content and main work of this paper and analyzes the main achievements and some areas that need to be improved
Summary
The world is in an era of fierce competition. e so-called competition is essentially the competition of talents. By optimizing the iterative process of cluster analysis algorithm, the valuable part of many students’ psychological data is extracted, and the data model is established to provide decision-making guidance for managers; scientific management of students’ mental health process can effectively improve the overall efficiency of psychological counseling and play an early warning role in the prevention of risk factors. For specific mental health problems, combined with a two-step cluster analysis, we use data mining techniques to find information from these data, to provide the basis for the planning and decision-making of mental health education. E fifth section is based on the mental health data mining of college students, combined with the actual clustering analysis algorithm research, and verifies the performance of the algorithm through implementation. E fourth section establishes the mental health data model based on the clustering analysis algorithm. e fifth section is based on the mental health data mining of college students, combined with the actual clustering analysis algorithm research, and verifies the performance of the algorithm through implementation. e sixth section summarizes the core content and main work of this paper and analyzes the main achievements and some areas that need to be improved
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