Relevance-Redundancy Dominance: a threshold-free approach to filter-based feature selection

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dc.contributor.authorBrowne, David
dc.contributor.authorManna, Carlo
dc.contributor.authorPrestwich, Steven D.
dc.contributor.editorGreene, Derek
dc.contributor.editorMacNamee, Brian
dc.contributor.editorRoss, Robert
dc.contributor.funderScience Foundation Irelanden
dc.date.accessioned2017-08-15T11:01:10Z
dc.date.available2017-08-15T11:01:10Z
dc.date.issued2016-09
dc.date.updated2017-08-15T10:25:30Z
dc.description.abstractFeature selection is used to select a subset of relevant features in machine learning, and is vital for simplification, improving efficiency and reducing overfitting. In filter-based feature selection, a statistic such as correlation or entropy is computed between each feature and the target variable to evaluate feature relevance. A relevance threshold is typically used to limit the set of selected features, and features can also be removed based on redundancy (similarity to other features). Some methods are designed for use with a specific statistic or certain types of data. We present a new filter-based method called Relevance-Redundancy Dominance that applies to mixed data types, can use a wide variety of statistics, and does not require a threshold. Finally, we provide preliminary results, through extensive numerical experiments on public credit datasets.en
dc.description.sponsorshipScience Foundation Ireland (Grant Number SFI/12/RC/2289)en
dc.description.statusPeer revieweden
dc.description.urihttp://aics2016.ucd.ie/en
dc.description.versionPublished Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationBrowne, D., Manna, C. and Prestwich, S. (2016) 'Relevance-Redundancy Dominance: a threshold-free approach to filter-based feature selection', in Greene, D., MacNamee, B. and Ross, R. (eds.) Proceedings of the 24th Irish Conference on Artificial Intelligence and Cognitive Science 2016, Dublin, Ireland, 20-21 September. CEUR Workshop Proceedings, 1751, pp. 227-238en
dc.identifier.endpage238en
dc.identifier.issn16130073
dc.identifier.journaltitleCEUR Workshop Proceedingsen
dc.identifier.startpage227en
dc.identifier.urihttps://hdl.handle.net/10468/4461
dc.identifier.volume1751en
dc.language.isoenen
dc.publisherSun SITE Central Europe / RWTH Aachen Universityen
dc.relation.ispartof24th Irish Conference on Artificial Intelligence and Cognitive Science 2016
dc.relation.urihttp://ceur-ws.org/Vol-1751/
dc.rights© 2016, David Browne, Carlo Manna and Steven Prestwich.en
dc.rights.urihttp://ceur-ws.org/en
dc.subjectFeature selectionen
dc.subjectMachine learningen
dc.subjectFilter-baseden
dc.subjectRelevance-Redundancy Dominanceen
dc.titleRelevance-Redundancy Dominance: a threshold-free approach to filter-based feature selectionen
dc.typeConference itemen
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