Bräuning, Michael and Hüllermeier, Eyke - Archives of Data Science, Series A

Article Details

Title Learning Conditional Lexicographic Preference Trees
Authors Bräuning, Michael and Hüllermeier, Eyke
Year 2014
Volume 1(1)
Abstract 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.