Prediction Method of Higher Vocational Students’ Psychological Health Education Achievements Based on Big Data Mining Technology

In view of the problem that the traditional prediction method lacks historical data, which leads to inaccurate prediction results, this paper proposes a prediction method for higher vocational students’ mental health education achievements based on big data mining technology. Under the curriculum knowledge map, combine big data mining technology to mine performance keywords. Hierarchical and classified education courses, determined the attribute set of achievement keywords to be mined, and calculated the similarity of two vectors and achievement keywords. According to the mining conditions given in NoSQL database, cluster the mining results, calculate the correlation degree between any two data, and build a performance prediction tree based on big data mining. Normalize the data through softmax, and design the process of score prediction. From the experimental results, it can be seen that this method has a precise prediction effect on the students’ scores of mental health education in personality development, adolescent mental health education, and learning.