Tag: streaming data

Researchers have introduced DACD, a dynamic adaptive learning method that detects concept drift in streaming data with a window-based CUSUM ...

Researchers have developed a feedback-guided framework that adapts decision thresholds instead of retraining classifiers, achieving near-equal accuracy with lower false ...

Researchers have developed MLIDSC, a self-adaptive online active learning framework that maintains high accuracy on multiclass imbalanced data streams while ...

Researchers have enhanced the SABeDM concept drift detector with KL divergence and a tolerance time mechanism, achieving consistently higher accuracy ...

Researchers have developed Hoeffding Adaptive Splitting Trees that combine periodic and change-driven splitting to improve ensemble classification of data streams ...