Employee Attrition Analysis Using XGBoost

In today's time, employee attrition is a major problem faced by organisations. The most precious resource for a firm is its workforce. They are the ones that bring values both quantitatively and qualitatively. A steady decline in the workforce due to resignation, death or retirement is referred to as attrition. It is a matter of concern when employees leave their jobs of better opportunities, but this leads the company to face its consequences. Employee turnover and attrition are equivalent. Leaders can avoid it by implementing better retention techniques by mastering this concept. In this paper, we use dataset to analyse attrition and determine the root cause of employee resignation. We did analysis of the training dataset for effective data exploration. Machine Learning algorithms, such as Random Forest Classifier, Logistic Regression, XGBoost and ensemble stacking technique were used. On data exploration and enabling algorithm we discovered that XGBoost classifier with an accuracy of 88. % and precision 89% was the most appropriate algorithm for this dataset. We may also conclude that monthly income, age, distance from home can be a reason behind employees leaving their job and finding better opportunities.