College Student Mental Health Analysis Based on Machine Learning Algorithm

The role of mental health in college students is very important, but there is a problem of low accuracy. In the past, psychological evaluation methods could not solve the problem of mental health evaluation among college students, and satisfaction was low. Therefore, this paper proposes a mechanical learning algorithm to construct a mental health evaluation system for college students. Firstly, the health scale is used to classify the mental health results, and the result collection is divided according to the scoring results, so as to realize the quantitative processing of mental health scores. The health scale then categorizes mental health outcomes, forms a collection of evaluation results, and iteratively analyzes mental health problems. MATLAB simulation shows that under the condition of certain health standards, the accuracy and stability of mental health results are better than those of previous psychological evaluation methods.