• Mathematics
  • Published 2011

Utility-Based Accuracy Measures to Empirically Evaluate Credal Classifiers

@inproceedings{Zaffalon2011UtilityBasedAM,
  title={Utility-Based Accuracy Measures to Empirically Evaluate Credal Classifiers},
  author={Marco Zaffalon and Giorgio Corani},
  year={2011}
}
Predictions made by imprecise-probability models are often indeterminate (that is, set-valued). Measuring the quality of an indeterminate prediction by a single number is important to fairly compare different models, but a principled approach to this problem is currently missing. In this paper we derive a measure to evaluate the predictions of credal classifiers from a set of assumptions. The measure turns out to be made of an objective component, and another that is related to the decision… CONTINUE READING

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