摘要
随着高职毕业生数量逐年增加,社会整体就业形势不容乐观,如何提升就业指导服务水平、改进教学管理工作是高职院校亟待解决的问题。近年来,数据挖掘技术快速发展,本文选取国内某高职院校若干毕业生的就业信息,利用决策树ID3算法构建模型,对高职毕业生就业情况进行预测,并由此得到影响毕业生就业的主要因素。通过模型可知,学业成绩、英语水平和有无工作经验是影响学生就业去向的主要因素。
With the number of higher vocational graduates increasing year by year,the overall social employment situation is not optimistic.How to improve the service level of employment guidance and improve teaching management is an urgent problem for higher vocational colleges.In recent years,with the rapid development of data mining technology,this paper selects the employment information of some domestic higher vocational college graduates,uses the decision tree ID3 algorithm to build a model to predict the employment situation of higher vocational graduates,and thus obtains the main factors affecting the employment of graduates.According to the model,academic achievement,English level and work experience are the main factors affecting the employment of students.
作者
李亚东
Li Yadong(Jiangsu Vocational College of Information Technology,Wuxi Jiangsu 214000,China)
出处
《信息与电脑》
2020年第17期54-56,共3页
Information & Computer
关键词
高职毕业生
决策树ID3算法
就业预测
vocational graduates
decision tree ID3 algorithm
employment forecast
作者简介
李亚东(1990-),男,江苏徐州人,硕士研究生,助教。研究方向:机器学习、就业创业研究。
