dc.contributor.author | Díez Peláez, Jorge | spa |
dc.contributor.author | Coz Velasco, Juan José del | spa |
dc.contributor.author | Bahamonde Rionda, Antonio | spa |
dc.contributor.author | Luaces Rodríguez, Óscar | spa |
dc.date.accessioned | 2013-01-30T12:38:53Z | |
dc.date.available | 2013-01-30T12:38:53Z | |
dc.date.issued | 2009 | spa |
dc.identifier.isbn | 978-3-642-04179-2 | |
dc.identifier.isbn | 978-3-642-04180-8 | |
dc.identifier.uri | http://hdl.handle.net/10651/12379 | |
dc.description | European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2009; Bled; 7 September 2009 through 11 September 2009 | |
dc.description.abstract | From a multi-class learning task, in addition to a classi er, it is possible to infer some useful knowledge about the relationship between the classes involved. In this paper we propose a method to learn a hierarchical clustering of the set of classes. The usefulness of such clusterings has been exploited in bio-medical applications to nd out relations between diseases or populations of animals. The method proposed here de nes a distance between classes based on the margin maximization principle, and then builds the hierarchy using a linkage procedure. Moreover, to quantify the goodness of the hierarchies we de ne a measure. Finally, we present a set of experiments comparing the scores achieved by our approach with other methods | |
dc.description.sponsorship | The research reported here is supported in part under grant TIN2008-06247 from the MICINN (Ministerio de Ciencia e Innovación of Spain) | |
dc.format.extent | p. 302-314 | spa |
dc.language.iso | eng | |
dc.publisher | Springer | |
dc.relation.ispartof | Machine Learning and Knowledge Discovery in Databases | spa |
dc.rights | © 2009 Springer | |
dc.title | Soft margin trees | spa |
dc.type | book part | spa |
dc.identifier.local | 20090165 | spa |
dc.identifier.doi | 10.1007/978-3-642-04180-8_37 | spa |
dc.relation.projectID | MICIIN/TIN2008-06247 | |
dc.relation.publisherversion | http://dx.doi.org/10.1007/978-3-642-04180-8_37 | spa |
dc.rights.accessRights | open access | |
dc.type.hasVersion | AM | |