Does an Efficient Calibrated Forecasting Strategy Exist?
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Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:809812, 2011.
Abstract
We recall two previouslyproposed notions of \emphasymptotic calibration for a forecaster making a sequence of probability predictions. We note that the existence of efficient algorithms for calibrated forecasting holds only in the case of binary outcomes. We pose the question: do there exist such efficient algorithms for the general (nonbinary) case?
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