Employee Attrition Rate Prediction - Using Machine Learning

Today, predicting employee attrition has become a significant issue for businesses. Organizations face a significant problem with employee attrition, particularly when highly skilled, knowledgeable, and important personnel depart in search of better opportunities elsewhere. The cost of replacing a trained employee is incurred as a result. Hence, we analyze data from both current and past employees to understand the prevalent causes of employee turnover. Employing established classification methods like decision trees, logistic regression, SVM, KNN, random forest, and naive Bayes, we leverage human resource data to proactively address employee attrition. Our approach involves implementing feature selection techniques on the data and scrutinizing the outcomes to mitigate the risk of employee loss. Businesses can grow more profitably by reducing the cost of their human resources when they can predict employee turnover.