Predictive Retraining: The Future of AI/ML in B5G Networks
Static retraining schedules fail in dynamic B5G networks. Our predictive approach uses unsupervised classifiers (e.g., Local Outlier Factor) to detect new traffic patterns and trigger just-in-time retraining, reducing SLA violations and resource waste. 🌟 Follow us on LinkedIn! Check…