Robust Ensemble Learning For Mining Noisy Data Streams

Elsevier Science Bv
Publication Type:
Journal Article
Decision Support Systems, 2011, 50 (2), pp. 469 - 479
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In this paper, we study the problem of learning from concept drifting data streams with noise, where samples in a data stream may be mislabeled or contain erroneous values. Our essential goal is to build a robust prediction model from noisy stream data t
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