利用人工智能技术对员工情绪下降趋势进行主动干预
Proactive Intervention to Downtrend Employee Attrition using Artificial Intelligence Techniques
摘要：
提前预测员工流失，使管理层能够采取个性化的预防措施。使用Entrance分类建模技术和线性回归。模型可以预测超过91%的准确率的员工预测，提前期在离职和个人原因造成的流失。事先告知员工流失使经理能够采取预防措施，以留住员工或管理流失的业务后果。该模型一旦实施，将有助于在员工态度下降的情况下，帮助管理者更有效地管理团队。模型不包括自然灾害，以及在个人层面发生的意外事件，如事故，死亡等。
英文摘要：
To predict the employee attrition beforehand and to enable management to take individualized preventive action. Using Ensemble classification modeling techniques and Linear Regression. Model could predict over 91% accurate employee prediction, lead-time in separation and individual reasons causing attrition. Prior intimation of employee attrition enables manager to take preventive actions to retain employee or to manage the business consequences of attrition. Once deployed this will model can help in downtrend Employee Attrition, will help manager to manage team more effectively. Model does not cover the natural calamities, and unforeseen events occurring at an individual level like accident, death etc.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
