Learning Conditional Lexicographic Preference Trees
Michael Bräuning, Eyke Hüllermeier · Repository KITopen (Karlsruhe Institute of Technology) · 2016
We introduce a generalization of lexicographic orders and argue that this generalization constitutes an interesting model class for preference learning in general and ranking in particular. We propose a learning algorithm for inducing a so-called conditional lexicographic preference tree from a given set of training data in the form of pairwise comparisons between objects. Experimentally, we validate our algorithm in the setting of multipartite ranking.