Research on Academic Buoyancy Classification Based on Iterative Decision Tree Algorithm

Abstract

The relationship between family risk factors and academic buoyancy has received attention through empirical studies, such as Bad family atmosphere, frequent family conflicts, disharmonious parent-child relationship, etc. Other family factors have an impact on the development of academic buoyancy, but there is less research on its combination characteristics. Based on the actual education scene of a middle school, we first score students’ academic buoyancy as the dependent variable and then collect nine types of variables representing family risk factors as independent variables. Then, a classification model between independent and dependent variables is constructed by using the decision tree method. The model provides a guideline for teaching work, and the test result of the model is ideal.