Active Cost-Sensitive Learning

@inproceedings{Margineantu2005ActiveCL,
  title={Active Cost-Sensitive Learning},
  author={Dragos D. Margineantu},
  booktitle={IJCAI},
  year={2005}
}
For many classification tasks a large number of instances available for training are unlabeled and the cost associated with the labeling process varies over the input space. Meanwhile, virtually all these problems require classifiers that minimize a nonuniform loss function associated with the classification decisions (rather than the accuracy or number of errors). For example, to train pattern classification models for a network intrusion detection task, experts need to analyze network events… CONTINUE READING

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