Early Detection of College Students' Psychological Problems Based on Decision Tree Model

The paper starts with the research on the early discovery of college students' psychological problems. Besides, it analyzes the data of the general survey of college students' mental health in a certain university, the existing data of students with psychological problems, and the questionnaire data of students' basic information in school. By comprehensively using the decision tree model and Kendall correlation analysis and other methods, using Python and SPSS software to preprocess the data and realize the model, it can obtain a psychological problem prediction model based on the objective behavior data of college students. The model is actually analyzed, and it gets good results.