943 citations · 1.1k across the 8 of their papers we have counts for
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Concept Drift Detection: Dealing with MissingValues via Fuzzy Distance Estimations
Anjin Liu, Jie Lu, Guangquan Zhang
In data streams, the data distribution of arriving observations at different time points may change - a phenomenon called concept drift. While detecting concept drift is a relative…
Concept Drift Detection via Equal Intensity k-means Space Partitioning
Anjin Liu, Jie Lu, Guangquan Zhang
Data stream poses additional challenges to statistical classification tasks because distributions of the training and target samples may differ as time passes. Such distribution ch…
Diverse Instances-Weighting Ensemble based on Region Drift Disagreement for Concept Drift Adaptation
Anjin Liu, Jie Lu, Guangquan Zhang
Concept drift refers to changes in the distribution of underlying data and is an inherent property of evolving data streams. Ensemble learning, with dynamic classifiers, has proved…
Learning under Concept Drift: A Review
Jie Lu, Anjin Liu, Fan Dong +3
Concept drift describes unforeseeable changes in the underlying distribution of streaming data over time. Concept drift research involves the development of methodologies and techn…