Decision tree algorithm based university graduate employment trend prediction

Abstract

The employment situation of college graduates is becoming more and more serious. It is of great significance to find effective methods to predict the employment trend of students. In this study, C4.5 algorithm was used to predict the employment trend of students. Taking the 2016 graduates of Henan University of Animal Husbandry and Economy as examples, four attributes affecting employment units were extracted, the information gain rate was calculated, the decision tree was constructed, and the classification rules were obtained. After data collection, conversion and cleaning, 420 employment records were obtained; 320 records were taken as the training samples. The classification rules were tested using 100 experimental samples, and the accuracy rate was 81%. Finally, the employment trend of the 2018 graduates was predicted by C4.5 algorithm, which provides a theoretical guidance for the arrangement of employment work in schools. Predicting the employment trend of students with decision tree algorithm is feasible and of great significance to the employment guidance of schools and the employment choice of students.