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Research on Mental Health Rating Algorithm Based on Big Data Classification Algorithm

In the era of big data, the industries of informatization construction and digital office are increasing, and big data mining has been widely used, which is both an opportunity and a challenge. Facing all kinds of data generated by society and people, it is imperative to classify them accurately, mine effective information and improve the utilization rate of information. College students, as a special group of society, are facing pressure from all sides, and there are more and more mental health problems, which lead to extreme events. How to find valuable information from huge test data has always been a difficult problem in the field of mental health testing. Based on Apriori algorithm, this paper researches association rules mining, finds out the relationship between the main factors and symptoms of college students' mental health, and provides support for solving college students' mental health problems and developing mental health test system. The research shows that Apriori improved algorithm reduces the workload of data calculation and improves the mining efficiency.