基于随机森林算法的人力资源可拓分析方法
An Extensive Analytical Approach on Human Resources using Random Forest Algorithm
摘要：
目前的工作调查显示，由于数据科学家、商业分析师和人工智能领域等近期工作的高薪，大多数软件员工正计划改变自己的工作角色。调查还表明，工作生活不平衡、低工资、轮班不均匀和许多其他因素也促使员工考虑改变工作生活。在本文中，一个有效的组织的公司在人力资源方面，该系统设计了一个模型的帮助下，考虑不同的员工参数的随机森林算法。这有助于人力资源部门通过识别差距来留住员工，并帮助组织以良好的员工保留率顺利运行。人力资源和数据科学的这种结合可以帮助组织员工的生产力，协作和福祉。它还有助于制定在外部和社会因素方面对员工绩效产生影响的战略。
英文摘要：
The current job survey shows that most software employees are planning to change their job role due to high pay for recent jobs such as data scientists, business analysts and artificial intelligence fields. The survey also indicated that work life imbalances, low pay, uneven shifts and many other factors also make employees think about changing their work life. In this paper, for an efficient organisation of the company in terms of human resources, the proposed system designed a model with the help of a random forest algorithm by considering different employee parameters. This helps the HR department retain the employee by identifying gaps and helping the organisation to run smoothly with a good employee retention ratio. This combination of HR and data science can help the productivity, collaboration and well-being of employees of the organisation. It also helps to develop strategies that have an impact on the performance of employees in terms of external and social factors.
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。
