BriefGPT.xyz
Jan, 2015
将C-bound推广到多类别和多标签设置
On Generalizing the C-Bound to the Multiclass and Multi-label Settings
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Francois Laviolette, Emilie Morvant, Liva Ralaivola, Jean-Francis Roy
TL;DR
该论文提供了一种将二元多数表决分类器风险紧密上限扩展到多类和多标签设置中的C-bound泛化方法。
Abstract
The
c-bound
, introduced in Lacasse et al., gives a tight upper bound on the risk of a
binary majority vote classifier
. In this work, we present a first step towards extending this work to more complex outputs, by
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