MDIE-AutoML: Multi-Detector Drift Detection with Dynamic Weighted Ensemble for Streaming AutoML
Non-stationary data streams suffer from simultaneous data and concept drifts that degrade model generalization. Conventional Automated Machine Learning for data streams, AML4S, relies on single-pipeline architecture with univariate ADWIN detection and exhaustive post-drift reconstruction, causing knowledge waste and in...