Convexity of Proper Composite Binary Losses
Date
2010
Authors
Reid, Mark
Williamson, Robert
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Publisher
Society for Artificial Intelligence and Statistics
Abstract
A composite loss assigns a penalty to a real-valued prediction by associating the prediction with a probability via a link function then applying a class probability estimation (CPE) loss. If the risk for a composite loss is always minimised by predicting the value associated with the true class probability the composite loss is proper. We provide a novel, explicit and complete characterisation of the convexity of any proper composite loss in terms of its link and its \weight function" associated with its proper CPE loss.
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Keywords
Keywords: Class probabilities; Weight functions; Artificial intelligence; Forecasting
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Source
Proceedings of The 13th International Conference on Artificial Intelligence and Statistics(AISTATS-2010)
Type
Conference paper
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Restricted until
2037-12-31
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