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Today's ever‐increasing generation of streaming data demands novel data mining approaches tailored to mining dynamic data streams. Data streams are non‐static in nature, continuously generated, and endless. They often suffer from class imbalance and undergo temporal drift. To address the classification of consecutive data instances within imbalanced data streams, this research introduces a new ensemble...
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