The Intelligent Prediction Model of College Students' Mental Health Based on Cluster Analysis Algorithm

Abstract

College life is a critical period of rapid psychological development and maturity of college students, and a key milestone in shaping students' healthy psychology. Help them form a healthy mind. The purpose of this paper is to study the intelligent model of students' mental health prediction based on cluster analysis algorithm. This paper analyzes the characteristics of students' mental health, analyzes the data sources, mainly discusses the mental health data used in this work, how to obtain the data and some issues that need to be considered when receiving the data. Combined with the actual cluster analysis algorithm research, the main purpose is to apply the cluster analysis algorithm to students' mental health education, analyze the real state of students' psychological problems, and combine the algorithm of this work to group. The correlation between the factors leading to students' psychological problems was analyzed, and some prediction results were obtained for the prediction of students' psychological difficulties. Boys are more decisive than girls in execution, and the t value is 9.55. The specific implementation steps and algorithm flow of the algorithm are given, and the performance of the algorithm is verified through implementation.