Based on the fact that the current research is not ideal for human salary management and per-formance optimization,a model which introduces machine learning is constructed to improve salary and per-formance.Based on XGBoost and GBDT algorithm,the influence of subjective and objective factors on sala-ry is studied.RMSE error analysis is carried out on the model accuracy rate through optimization,and the accuracy rate of XGBoost algorithm model is RMSE22.36 and that of GBDT algorithm model is 39.85.The analytic hierarchy process is used to study and evaluate the weight of each performance indicator,which re-alizes the scientific setting of performance indicators and the dynamic adjustment of data monitoring under the framework of machine learning,and verifies the effectiveness of this model for the research of human salary management and performance optimization system.
关键词
机器学习/薪资管理/绩效优化/动态调整/层次分析法
Key words
machine learning/salary management/performance optimization/dynamic adjustment/ana-lytic hierarchy process
维普
万方数据