Application of Machine Learning Techniques for Decision Making Process in Human Resource Management

Abstract

The strategic alignment between organisational objectives and human resource management is stronger in contemporary organizations. As deep learning methods and machine learning solutions play a larger role in managing human resource management operations, organizations are focusing on more applicable sets of solutions. Models based on machine learning are now making progress in a variety of HRM-related fields. Machine learning is being used in human resource management to anticipate who will remain and who will depart the company, as well as to gauge workers' interest in their specific organisation.Data scraping methods are used to extract the data, which is then saved in CSV format. With the aid of ML algorithms, the many characteristics in the data acquired using this method may be used to make predictions. The management may develop a strategy to keep a deserving person in the organization by using the analysis to draw conclusions about who will remain or depart the company.We used a variety of methods in our investigation, including feature scaling and SMOTE. The recommended techniques, such as random forest and XG boost classifier, are supported by the findings. We'll arrive to a judgment based on the accuracy rate (%) numbers for the results generated by the offered approaches. © 2023 IEEE.