A Comparative Analysis of MLR, SVR, and KNN for Improving Quality of Service in Next Generation Network via Machine Learning Regression

An age of unprecedented connectivity has begun with the rollout of 5G networks, which promise huge device connectivity, minimal latency, and high data speeds. Ensuring Quality of Service (QoS) in these intricate and ever-changing networks is still a formidable task, though. To improve and optimize the quality of service (QoS) in 5G networks, this study investigates the use of machine learning regression techniques, including Multiple Linear Regression (MLR), Support Vector Regression (SVR), and k-Nearest Neighbors Regression (KNN). To assess how well these algorithms forecast and optimize important QoS parameters, a comparative analysis is done.