基于分类器的员工离职预测研究  

Research on Employee Turnover Prediction Based on Classifier

作　　者：覃奕璇 温红艳 QIN Yi-xuan;WEN Hong-yan(School of Electrical and Electronic Engineering,Wuhan Polytechnic University,Wuhan 430023,China)

机构地区：[1]武汉轻工大学电气与电子工程学院,湖北武汉430023

出　　处：《电脑与信息技术》2024年第2期54-56,130,共4页Computer and Information Technology

基　　金：2022年湖北省大学生创新创业训练计划项目(项目编号:S202210496029)。

摘　　要：人才是企业的核心竞争力,优秀员工的离职不仅会给企业业务和生产造成损失,人员的流动更会带来企业凝聚力的降低。运用机器学习算法,对导致员工离职的因素加以研究分析,能够有效为企业避免员工的流失,保证企业的市场竞争力。通过四种不同分类器对员工离职样本库进行建模,预测分析结果表明,逻辑回归分类器的准确率最高,较好地预测了员工的离职意向。Talent is the core competitiveness of enterprises.The turnover of outstanding employees will not only cause losses to the business and production of enterprises,but also reduce the cohesion of enterprises.Using machine learning algorithm to study and analyze the factors that lead to employee turnover can effectively avoid the loss of employees and ensure the market competitiveness of enterprises.Four different classifiers were used to model the employee turnover sample database.The results of prediction analysis show that the logistic regression classifier has the highest accuracy and can predict the employee turnover intention well.

关 键 词：离职预测 线性分类器 数据可视化 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]