2020/12/02 by Shenghuan Yang, Tariqul Islam, Yang, Shenghuan +1
Business, Management and Accounting · #AI and HR Technologies #Computers and Society (cs.CY) #Customer churn and segmentation #Employer Branding and e-HRM #FOS: Computer and information sciences
paper · pdf · doi:10.48550/arxiv.2012.01286
openalex publication_date 2020/12/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.