Active Learning for Unbalanced Data in the Challenge with Multiple Models and Biasing

@inproceedings{Chen2011ActiveLF,
  title={Active Learning for Unbalanced Data in the Challenge with Multiple Models and Biasing},
  author={Yi Chen and S. Mani},
  booktitle={Active Learning and Experimental Design @ AISTATS},
  year={2011}
}
  • Yi Chen, S. Mani
  • Published 2011 in Active Learning and Experimental Design @ AISTATS
The common uncertain sampling approach searches for the most uncertain samples closest to the decision boundary for a classification task. However, we might fail to find the uncertain samples when we have a poor probabilistic model. In this work, we develop an active learning strategy called “Uncertainty Sampling with Biasing Consensus” (USBC) which predicts the unbalanced data by multi-model committee and ranks the informativeness of samples by uncertainty sampling with higher weight on the… CONTINUE READING
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