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Analysis and Prediction of Employee Turnover Characteristics based on Machine Learning

机译:基于机器学习的员工离职特征分析与预测

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Employee turnover indicates the staff decides to leave the company. Along with the fast development of economic and industries, employee turnover phenomenon becomes popular gradually in recent years. On one hand, the staff decides to leave the company due to various reasons. On the other hand, staff retention and job stability impact the normal operation of the company. Companies need to grasp the major factors of employee turnover, and then take relevant measures to deal with this problem. This paper employs machine learning technique to sort out the characteristics of employee turnover. Furthermore, we adopt GBDT algorithm and LR algorithm to fit the characteristic model which influences employee turnover. Finally, this paper implements the employee turnover prediction in realistic companies, which provides an effective reference for companies to reduce the turnover rate of employees.
机译:员工流失表明员工决定离开公司。随着经济和工业的快速发展,员工流失现象近年来逐渐流行起来。一方面,由于各种原因,员工决定离开公司。另一方面,员工保留和工作稳定性会影响公司的正常运营。公司需要掌握员工离职的主要因素,然后采取相应的措施来解决这个问题。本文采用机器学习技术来梳理员工离职的特点。此外,我们采用GBDT算法和LR算法来拟合影响员工流动的特征模型。最后,本文对现实公司的员工离职率进行了预测,为企业降低员工离职率提供了有效的参考。

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