Employee Performance Measurement Using Machine Learning Algorithms

Employee performance measurement is a critical aspect of organizational management, aiming to assess and improve the productivity, efficiency, and effectiveness of employees. With the advancement of technology, machine learning (ML) has emerged as a powerful tool in enhancing how organizations measure and manage employee performance. This work implements three machine learning models such as Support Vector Classifier (SVC), Random Forest (RF) and Multi Layered Perceptron (MLP). The training accuracy of support vector classifier model 97.63% and testing accuracy is 95.15%. The training accuracy of Random Forest model 100% and testing accuracy is 92.25%. The training accuracy of MLP model 99.63% and testing accuracy is 96.61%. This clearly shows that MLP model performs better in this case with highest accuracy.