Research on Data Mining of College Students' Psychological Problems Based on Apriori Algorithm

Faced with the severe mental health situation of college students, colleges and universities have designed and launched a series of mental health screening programs to obtain students' true mental state, so as to support the follow-up mental health guidance. However, there are many limitations in the traditional investigation and evaluation methods used in colleges and universities at present, which are difficult to meet the actual needs of mental health guidance in colleges and universities. In view of the above problems, this paper will deeply study the application feasibility of data mining technology in this field, and put forward a brand-new data analysis model of college students' mental health, so as to obtain the potential relationship between psychological problems and multidimensional data information, thus providing scientific basis for mental health guidance in colleges and universities. Practice has proved that the whole model takes Apriori algorithm as the core, and by analyzing the data of students' mental health questionnaire, the correlation between students' psychological problems and students' behavioral characteristics is found, so as to promote the designation and implementation of personalized intervention measures and provide new ideas for the accurate and scientific development of mental health education in colleges and universities.