@inproceedings{zaffalon2011isipta,
 abstract = {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-maker's degree of risk-aversion. We discuss
when the measure can be rendered independent of such a
degree, and provide insights as to how the comparison
of classifiers based on the new measure change with the
number of predictions to be made. Finally, we
empirically study the behavior of the proposed
measure.},
 address = {Innsbruck, Austria},
 author = {Marco Zaffalon and Giorgio Corani and Denis Deratani
Mauá},
 booktitle = {ISIPTA '11: Proceedings of the Seventh International
Symposium on Imprecise Probability: Theories and
Applications},
 editor = {F. Coolen and Gert de Cooman and T. Fetz and M.
Oberguggenberger},
 keywords = {credal classification,credal classifiers,discounted
accuracy,empirical,evaluation,indeterminacy,risk-aversion,utility},
 pages = {401--410},
 publisher = {SIPTA},
 title = {Utility-Based Accuracy Measures to Empirically
Evaluate Credal Classifiers},
 url = {http://leo.ugr.es/sipta/isipta11/proceedings/papers/s016.pdf},
 year = {2011}
}