Distance-Based Decision Tree Algorithms for Label Ranking
Distance-Based Decision Tree Algorithms for Label Ranking
dc.contributor.author | Cláudio Rebelo Sá | en |
dc.contributor.author | Rebelo,C | en |
dc.contributor.author | Carlos Manuel Soares | en |
dc.contributor.author | Knobbe,A | en |
dc.date.accessioned | 2017-12-12T15:59:37Z | |
dc.date.available | 2017-12-12T15:59:37Z | |
dc.date.issued | 2015 | en |
dc.description.abstract | The problem of Label Ranking is receiving increasing attention from several research communities. The algorithms that have developed/adapted to treat rankings as the target object follow two different approaches: distribution-based (e.g., using Mallows model) or correlation-based (e.g., using Spearman's rank correlation coefficient). Decision trees have been adapted for label ranking following both approaches. In this paper we evaluate an existing correlation-based approach and propose a new one, Entropy-based Ranking trees. We then compare and discuss the results with a distribution-based approach. The results clearly indicate that both approaches are competitive. | en |
dc.identifier.uri | http://repositorio.inesctec.pt/handle/123456789/3924 | |
dc.identifier.uri | http://dx.doi.org/10.1007/978-3-319-23485-4_52 | en |
dc.language | eng | en |
dc.relation | 5527 | en |
dc.relation | 5001 | en |
dc.rights | info:eu-repo/semantics/openAccess | en |
dc.title | Distance-Based Decision Tree Algorithms for Label Ranking | en |
dc.type | conferenceObject | en |
dc.type | Publication | en |
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