论文标题
IBM员工流失分析
IBM Employee Attrition Analysis
论文作者
论文摘要
在本文中，我们分析了数据集IBM员工损耗，以找到员工选择辞职的主要原因。首先，我们利用了相关矩阵来查看某些与其他属性没有显着相关并将其从数据集中删除的功能。其次，我们通过利用随机森林，发现每月元素，年龄以及公司数量的工作对员工流失产生重大影响来选择重要特征。接下来，我们还通过使用K-均值聚类将人们分为两个群集。最后，我们进行了二进制逻辑回归的定量分析：经常旅行的人的损耗是很少旅行的人的2.4倍。而且我们还发现，在人力资源工作的员工离开离开。
In this paper, we analyzed the dataset IBM Employee Attrition to find the main reasons why employees choose to resign. Firstly, we utilized the correlation matrix to see some features that were not significantly correlated with other attributes and removed them from our dataset. Secondly, we selected important features by exploiting Random Forest, finding monthlyincome, age, and the number of companies worked significantly impacted employee attrition. Next, we also classified people into two clusters by using K-means Clustering. Finally, We performed binary logistic regression quantitative analysis: the attrition of people who traveled frequently was 2.4 times higher than that of people who rarely traveled. And we also found that employees who work in Human Resource have a higher tendency to leave.
