Periodic Retraining Beats Drift Detection by Up to 55% on Static Models
The arXiv study by Sawan Dasari, based on 4,000 experiments, shows that for models that cannot learn incrementally, a simple periodic-retraining schedule outperforms both error-threshold and drift-detection policies, delivering 15-55 percentage-point accuracy gains while cutting infrastructure compl