Prediction of Employee Attrition Using Machine Learning and Ensemble Methods

Employees are the most valuable resources for any organization. The cost associated with professional training, the developed loyalty over the years and the sensitivity of some organizational positions, all make it very essential to identify who might leave the organization. Many reasons can lead to employee attrition. In this paper, several machine learning models are developed to automatically and accurately predict employee attrition. IBM attrition dataset is used in this work to train and evaluate machine learning models; namely Decision Tree, Random Forest Regressor, Logistic Regressor, Adaboost Model, and Gradient Boosting Classifier models. The ultimate goal is to accurately detect attrition to help any company to improve different retention strategies on crucial employees and boost those employee satisfactions.