Tag: data streams

Researchers at Sichuan University have developed a collaborative framework that combines multi-window concept drift detection with an evolving fuzzy system ...

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

Researchers at the University of Bologna have developed DSC+, a two-phase streaming clustering algorithm that profiles the evolving schemas of ...

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

Researchers in Pakistan have developed a real-time method that detects machine learning model drift in fog computing healthcare systems without ...

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

Researchers in China have developed CADEE, an online ensemble learning framework that simultaneously handles multi-class imbalance, concept drift, and limited ...