Sasthakumar Ramamurthy

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Streaming data may consist of multiple drifting concepts each having its own underlying data distribution. We present an ensemble learning based approach to handle the data streams having multiple underlying modes. We build a global set of classifiers from sequential data chunks; ensembles are then selected from this global set of classifiers, and new(More)
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