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.
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🌟 Full paper in: https://zenodo.org/records/11045683