Research on the Application of Data Mining Based on Deep Learning in the Analysis of Psychoeducational Factors

Abstract

The role of psychoeducational factor analysis in college students’ psychological counseling education is very important, but there is a problem of inaccurate outcome evaluation. The traditional education model cannot solve the problem of factor analysis and evaluation in college students’ psychological counseling education, and the evaluation is unreasonable. Therefore, this paper proposes a data mining algorithm to perform optimization factor analysis and evaluation analysis. Firstly, cognitive theory is used to evaluate the influencing factors, and the indicators are divided according to the requirements of factor analysis and evaluation, so as to reduce the interference factors in factor analysis and evaluation. Then, cognitive theory analyzes and evaluates the factors affecting the mental health of college students, forms a factor analysis and evaluation scheme, and comprehensively analyzes the factor analysis and evaluation results. MATLAB simulation shows that under certain evaluation criteria, the data mining algorithm is better than the traditional education model in analyzing and evaluating the factors affecting the mental health of college students.