An adaptive learning approach for noisy data streams

@article{Chu2004AnAL,
  title={An adaptive learning approach for noisy data streams},
  author={Fang Chu and Yizhou Wang and Carlo Zaniolo},
  journal={Fourth IEEE International Conference on Data Mining (ICDM'04)},
  year={2004},
  pages={351-354}
}
Two critical challenges typically associated with mining data streams are concept drift and data contamination. To address these challenges, we seek learning techniques and models that are robust to noise and can adapt to changes in timely fashion. We approach the stream-mining problem using a statistical estimation framework, and propose a fast and robust discriminative model for learning noisy data streams. We build an ensemble of classifiers to achieve timely adaptation by weighting… CONTINUE READING
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