Elicitation and identification of properties
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Steinwart, Ingo
Pasin, Chloé
Williamson, Robert C.
Zhang, Siyu
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Abstract
Properties of distributions are real-valued functionals such as the mean, quantile or conditional value at risk. A property is elicitable if there exists a scoring function such that minimization of the associated risks recovers the property. We extend existing results to characterize the elicitability of properties in a general setting. We further relate elicitability to identifiability (a notion introduced by Osband) and provide a general formula describing all scoring functions for an elicitable property. Finally, we draw some connections to the theory of coherent risk measures.
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Journal of Machine Learning Research
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