Improving classifier utility by altering the misclassification cost ratio

@inproceedings{Ciraco2005ImprovingCU,
  title={Improving classifier utility by altering the misclassification cost ratio},
  author={Michelle Ciraco and Michael Rogalewski and Gary Weiss},
  booktitle={UBDM '05},
  year={2005}
}
This paper examines whether classifier utility can be improved by altering the misclassification cost ratio (the ratio of false positive misclassification costs to false negative misclassification costs) associated with two-class datasets. This is evaluated by varying the cost ratio passed into two cost-sensitive learners and then evaluating the results using the actual (or presumed actual) cost information. Our results indicate that a cost ratio other than the true ratio often maximizes… CONTINUE READING
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UCI Repository of machine learning databases [http://www.ics.uci.edu/~mlearn/ MLRepository.html

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