Employee Performance Prediction for Workforce Planning using Ensemble Hybrid Model

HRM (Human Resource Management) plays a major role in identifying t talented employees in the organization. The growth of an organization depends upon the involvement and performance of the employees. A well-performed Employee is always an asset to an organization. In this study, talented employees in the organization are identified using the Classification technique. To predict their performance, various employee attributes are collected from the reputed organization. Machine Learning algorithms are used to enable HR professionals and decision-makers to predict and enhance employee performance. Here we propose Ensemble XG Boost Random Forest Hybrid Algorithm (EXGBRF) algorithm to precise its prediction. The result shows 100 percent of accuracy.