2014
COLT
COLT 2014
Elicitation and Identification of Properties
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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Interdisciplinary Bridge
— Machine Learning and Mathematics & Optimization
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Trend Setter
— Loss Functions
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Keyword Pioneer
— elicitable property
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Cross-Pollinator
— Artificial Intelligence, Machine Learning, Mathematics & Optimization
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Hot Topic Early Bird
— probabilistic modeling
Authors
Topics
Machine Learning > Optimization & Theory > Loss Functions
Machine Learning > Optimization & Theory > Statistical Learning
Mathematics & Optimization > Mathematics > Probability
Mathematics & Optimization > Optimization > Optimization
Mathematics & Optimization > Statistics
Machine Learning > Optimization & Theory > Statistics