Pairwise Preference Learning and Ranking

  title={Pairwise Preference Learning and Ranking},
  author={Johannes F{\"u}rnkranz and Eyke H{\"u}llermeier},
We consider supervised learning of a ranking function, which is a mapping from instances to total orders over a set of labels (options). The training information consists of examples with partial (and possibly inconsistent) information about their associated rankings. From these, we induce a ranking function by reducing the original problem to a number of binary classification problems, one for each pair of labels. The main objective of this work is to investigate the trade-off between the… 
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