Feature Classification and Modeling of Group Psychological Anxiety Based on Big Data Analysis Technology

Abstract

With the rapid development of Chinese society, mental health problems have become increasingly prominent and an important public health challenge. This study focuses on the use of big data and machine learning technology and puts forward DeepPsy model, which is a special algorithm for identifying students' mental health problems. DeepPsy model has significantly improved the recognition rate, especially the recall rate, which means that the model can identify students with potential mental health problems more comprehensively. At the same time, it is discussed that different feature combinations are very important for model performance to improve recognition accuracy. The historical data analysis module is introduced to enhance the intuitive interpretation of the data, and the total score and trend analysis of various factors are retained.