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A hybrid loss for multiclass and structured prediction

Shi, Qinfeng; Reid, Mark; Caetano, Tiberio; van den Hengel, Anton; Wang, Zhenhua


We propose a novel hybrid loss for multiclass and structured prediction problems that is a convex combination of a log loss for Conditional Random Fields (CRFs) and a multiclass hinge loss for Support Vector Machines (SVMs). We provide a sufficient condition for when the hybrid loss is Fisher consistent for classification. This condition depends on a measure of dominance between labels - specifically, the gap between the probabilities of the best label and the second best label. We also prove...[Show more]

CollectionsANU Research Publications
Date published: 2015
Type: Journal article
Source: IEEE Transactions on Pattern Analysis and Machine Intelligence
DOI: 10.1109/TPAMI.2014.2306414


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