Tag: concept drift

A PLOS Complex Systems opinion article argues that AI embedded in complex systems needs meta-cognitive abilities to detect when its ...

A new adaptive learning framework combines temporal decay weighting, sliding-window retraining and closed-loop SHAP explanations to keep intrusion detection accurate ...

A label-free Incremental PCA method produced a smooth internal-reliability signal across industrial and wireless sensor streams, but its response to ...

WeanNet progressively withdraws a parent network’s lateral influence from a student, improving adaptation in a controlled concept-drift task while enabling ...

The abstract reports that rank fusion improved evasive- and novel-family malware detection across three longitudinal benchmarks, while fixed-threshold testing over ...

A systematic review of 200 studies finds machine learning effective for detecting DDoS and ARP spoofing attacks on university networks, ...

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 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 ...