Construction and Application of Machine Learning Algorithm in Mental Health Teacher Competency Model

The role of machine learning algorithms in constructing mental health teacher competency models is very important, but there is a problem of low construction accuracy. Standard competency models are poorly constructed and cannot solve many aspects of psychoanalysis. Therefore, this paper proposes a machine learning algorithm and a mental health teacher competency model. Firstly, the competency theory is used to classify mental health teachers, and the competency construction scheme is selected according to the mental health teaching standards. Then, a building set is formed according to the competency criteria, and the competency parameters are iteratively judged. MATLAB simulations show that in mental health teachers, machine learning algorithms can improve competency accuracy and shorten construction Time, the results were better than the standard competency model.