Application of decision tree algorithm mining model in career planning goal simulation

Abstract

Abstract To help college students choose their first career type, the author proposes an application method of a decision tree algorithm mining model in constructing a career planning goal model. The author uses OLAP technology to study and analyze the internal factors such as gender, personality, temperament, and interest of college students, as well as the career type that college students choose for the first time, excavate the potential law between the career type that college students choose for the first time and the internal factors of students, and apply it to the choice of college students’ first career type. The actual results show that the overall accuracy of the mining model is quite high when 50% of the data is used to obtain 50% of the target. The prediction accuracy of the decision tree model in 50% of the data is 47.14%. When the amount of data is 100%, the prediction accuracy of the model reaches 94.29%. The prediction accuracy of the actual decision tree model in 50% of the data is 47.14%. When the amount of data reaches 100%, the prediction accuracy of the model is 68.57%.