Artificial Intelligence enabled Employee Performance Prediction using Comprehensive Learning Metrics

Human capital is crucial to the success of businesses in the new knowledge economy. There is a compelling financial justification for developing a system to assess and enhance employee performance, making performance measurement at the level of the individual worker a must. With Data Mining, HR professionals may find new and relevant information (HRM). The success of an employee is not dependent on a single trait. Humans vary greatly in their innate talents and the traits that define their personalities. Hence, data from many sectors must be collected for performance monitoring. The purpose of this article is to present an overall grade of an employee's performance taking into account a number of criteria. We begin by contrasting many popular Machine Learning algorithmsagainst one another. We then recommend an ensemble method that draws from the aforementioned methods. The empirical findings show that the suggested model outperforms the state-of-the-art models in terms of precision, recall, F1-score, and accuracy, as compared to the more conventional models.