Model Testing and Validation of Factors Affecting Wellbeing of Retail Salesforce: Harnessing Machine Learning for Wireless Channel Prediction in Retail Environments

This abstract focus on model testing and validation of factors affecting the wellbeing of retail salesforce, with a particular emphasis on utilizing machine learning for wireless channel prediction in retail environments. The study aims to identify and understand the key factors that influence the wellbeing of retail salesforce, such as workload, job satisfaction, and work-life balance. By applying machine learning techniques to analyze wireless channel data in retail settings, the study seeks to predict and optimize wireless communication performance, ultimately enhancing the efficiency and productivity of the retail workforce. The findings of this research have implications for improving the working conditions and overall wellbeing of retail salesforce, while also leveraging advanced technologies for enhancing wireless communication in retail environments.