随机森林算法在高校毕业生离校未就业问题中的应用

Application of Random Forest Algorithm to the Problem of College Graduate without Employment

基于某校五年的就业历史数据,构建大学生“未就业”预测模型,预测准确率和召回率均达到85%以上。并对未就业的学生的共同特点进行挖掘,找出和未就业相关的影响因素和影响程度。该模型可以帮助学生个体客观评估个人能力,降低期待,有针对性的弥补短板,提高就业能力。同时帮助就业学生工作部门找出就业困难的学生群体,进行有针对性的就业指导,对于大学生就业工作有一定的指导意义。

Based on the employment historical data of a university for five years,this paper constructs a prediction model of college students’“unemployed”,and the prediction accuracy and recall rate are both above 85%.The common characteristics of the unemployed students are excavated to find out the factors and the degree of influence related to the unemployed.This model can help students objectively assess their abilities,reduce their expectations,make up for their weaknesses and improve their employability.At the same time,it can help the employment of students work department to find out the difficulties in employment of student groups,target employment guidance.For the employment of college students it has a certain guiding significance.