SERA: Selectively recursive approach towards nonstationary imbalanced stream data mining

@article{Chen2009SERASR,
  title={SERA: Selectively recursive approach towards nonstationary imbalanced stream data mining},
  author={Sheng Chen and Haibo He},
  journal={2009 International Joint Conference on Neural Networks},
  year={2009},
  pages={522-529}
}
Recent years have witnessed an incredibly increasing interest in the topic of stream data mining. Despite the great success having been achieved, current approaches generally assume that the class distribution of the stream data is relatively balanced. However, in applications such as network intrusion detection, credit fraud detection, spam classification, and many others, the class distribution is mostly imbalanced and the cost for misclassifying a minority example is very expensive. Concept… CONTINUE READING
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