Gradient-based Label Binning in Multi-label Classification

  title={Gradient-based Label Binning in Multi-label Classification},
  author={Michael Rapp and Eneldo Loza Menc{\'i}a and Johannes F{\"u}rnkranz and Eyke H{\"u}llermeier},
In multi-label classification, where a single example may be associated with several class labels at the same time, the ability to model dependencies between labels is considered crucial to effectively optimize non-decomposable evaluation measures, such as the Subset 0/1 loss. The gradient boosting framework provides a well-studied foundation for learning models that are specifically tailored to such a loss function and recent research attests the ability to achieve high predictive accuracy in… Expand
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