Exploiting propositionalization based on random relational rules for semi-supervised learning

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dc.contributor.authorPfahringer, Bernhard
dc.contributor.authorAnderson, Grant
dc.coverage.spatialConference held at Osaka, Japanen_NZ
dc.date.accessioned2008-11-20T22:07:03Z
dc.date.available2008-11-20T22:07:03Z
dc.date.issued2008
dc.description.abstractIn this paper we investigate an approach to semi-supervised learning based on randomized propositionalization, which allows for applying standard propositional classification algorithms like support vector machines to multi-relational data. Randomization based on random relational rules can work both with and without a class attribute and can therefore be applied simultaneously to both the labeled and the unlabeled portion of the data present in semi-supervised learning. An empirical investigation compares semi-supervised propositionalization to standard propositionalization using just the labeled data portion, as well as to a variant that also just uses the labeled data portion but includes the label information in an attempt to improve the resulting propositionalization. Preliminary experimental results indicate that propositionalization generated on the full dataset, i.e. the semi- supervised approach, tends to outperform the other two more standard approaches.en_US
dc.identifier.citationPfahringer, B. & Anderson, G. (2008). Exploiting propositionalization based on random relational rules for semi-supervised learning. In T. Washio et al. (Eds), Proceedings of 12th Pacific-Asia Conference, PAKDD 2008 Osaka, Japan, May 20-23, 2008(pp. 495-502). Berlin: Springer.en_US
dc.identifier.doi10.1007/978-3-540-68125-0_43en_US
dc.identifier.urihttps://hdl.handle.net/10289/1428
dc.language.isoen
dc.publisherSpringer, Berlinen_US
dc.relation.isPartOfProc Twelfth Pacific-Asia Conference: Advances in Knowledge Discovery and Data Miningen_NZ
dc.relation.urihttp://www.springerlink.com/content/w76142141408x063/en_US
dc.sourcePAKDD 2008en_NZ
dc.subjectcomputer scienceen_US
dc.subjectsemi-superviseden_US
dc.subjectpropositionalizationen_US
dc.subjectrandomizationen_US
dc.subjectMachine learning
dc.titleExploiting propositionalization based on random relational rules for semi-supervised learningen_US
dc.typeConference Contributionen_US
pubs.begin-page494en_NZ
pubs.elements-id17700
pubs.end-page502en_NZ
pubs.finish-date2008-05-23en_NZ
pubs.start-date2008-05-20en_NZ
pubs.volumeLecture Notes in Artificial Intelligence 5012en_NZ
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