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Learning Conditional Lexicographic Preference Trees

Bräuning, Michael; Hüllermeier, Eyke

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.


Zugehörige Institution(en) am KIT Institut für Informationswirtschaft und Marketing (IISM)
Publikationstyp Zeitschriftenaufsatz
Jahr 2016
Sprache Englisch
Identifikator DOI: 10.5445/KSP/1000058747/03
ISSN: 2363-9881
URN: urn:nbn:de:swb:90-677616
KITopen ID: 1000067761
Erschienen in Archives of Data Science, Series A
Band 1
Heft 1
Seiten 41-55
Lizenz CC BY-SA 3.0 DE: Creative Commons Namensnennung – Weitergabe unter gleichen Bedingungen 3.0 Deutschland
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