Comparison of Ranking Procedures in Pairwise Preference Learning
نویسندگان
چکیده
Computational methods for discovering the preferences of individuals are useful in many applications. In this paper, we propose a method for learning valued preference structures, using a natural extension of so-called pairwise classification. A valued preference structure can then be used in order to induce a ranking, that is a linear ordering of a given set of alternatives. This step is realized by means of a so-called ranking procedure. In the second part of the paper, we compare the performance of alternative ranking procedures in an experimental way.
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