Active Learning with Committees for Text Categorization

  title={Active Learning with Committees for Text Categorization},
  author={Ray Liere and Prasad Tadepalli},
In many real-world domains, supervised learning requires a large number of training examples. In this paper, we describe an active learning method that uses a committee of learners to reduce the number of training examples required for learning. Our approach is similar to the Query by Committee framework, where disagreement among the committee members on the predicted label for the input part of the example is used to signal the need for knowing the actual value of the label. Our experiments… CONTINUE READING
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