Research And Application Of Decision Tree Technology In Mental Health Assessment Of College Students

With the development of society,mental health has become a basic standard for college students to grow into qualified talents.At present,the psychological problems of college students have attracted great attention from all walks of life.Especially for private college students,students are facing the pressure of employment and postgraduate entrance examination,and so on.There may be more psychological problems,which requires In-depth study on college students' mental health status and psychological intervention measures.The purpose of this study is to use data mining principles and methods to mine the factors that lead to psychological problems of College students,and to objectively intervene psychologically.On the basis of introducing the background of the subject and the theory of data mining,this thesis takes the psychological data collected by 2016 freshmen of a college in Henan Province as the research object,builds the data analysis model,elaborates the data preprocessing method in detail,and uses Apriori algorithm to treat obsessivecompulsive symptoms,interpersonal sensitivity symptoms and psychological questions.Based on the results of mining association patterns mentioned above,a decision tree ID3 algorithm is used to establish a decision-making model for positive symptoms of sensitive symptoms of interpersonal relationship.The data mining related technologies and algorithms are used to synthesize the two algorithms.The mining results are fed back to psychological counselors,which provides a theoretical basis for the evaluation and intervention of college student's mental health.