A transformer-based deep learning framework to predict employee attrition.

ABSTRACT: In all areas of business, employee attrition has a detrimental impact on the accuracy of profit management. With modern advanced computing technology, it is possible to construct a model for predicting employee attrition to minimize business owners' costs. Despite the reality that these types of models have never been evaluated under real-world conditions, several implementations were developed and applied to the IBM HR Employee Attrition dataset to evaluate how these models may be incorporated into a decision support system and their effect on strategic decisions. In this study, a Transformer-based neural network was implemented and was characterized by contextual embeddings adapting to tubular data as a computational technique for determining employee turnover. Experimental outcomes show

SUBMITTER: Li W 

PROVIDER: S-EPMC10557501 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature