This work focuses on a particular application of preference ranking, wherein the problem is to learn a mapping from instances to rankings over a finite set of labels, i.e. label ranking. Our approach is based on a learning reduction technique and provides such a mapping in the form of logical rules: if [antecedent] then [consequent], where [antecedent] contains a set of conditions, usually connected by a logical conjunction operator (AND) while [consequent] consists in a ranking among labels. The approach presented in this paper mainly comprises five phases: preprocessing, rules generation, post-processing, classification and ranking generation.
|Title of host publication||Advances on computational intelligence: 14th international conference on information processing and management of uncertainty in knowledge-based systems, proceedings, part 1|
|Editors||Salvatore Greco, B. Bouchon-Meunier, G. Coletti, M. Fedrizzi, B. Matarazzo, R. Yager|
|Place of Publication||Berlin|
|Number of pages||11|
|Publication status||Published - 2012|
|Name||Communications in computer and information science|