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

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dc.contributor.author Browne, David
dc.contributor.author Manna, Carlo
dc.contributor.author Prestwich, Steven D.
dc.contributor.editor Greene, Derek
dc.contributor.editor MacNamee, Brian
dc.contributor.editor Ross, Robert
dc.date.accessioned 2017-08-15T11:01:10Z
dc.date.available 2017-08-15T11:01:10Z
dc.date.issued 2016-09
dc.identifier.citation Browne, 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. 227-238 en
dc.identifier.volume 1751 en
dc.identifier.startpage 227 en
dc.identifier.endpage 238 en
dc.identifier.issn 16130073
dc.identifier.uri http://hdl.handle.net/10468/4461
dc.description.abstract Feature 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.sponsorship Science Foundation Ireland (Grant Number SFI/12/RC/2289) en
dc.description.uri http://aics2016.ucd.ie/ en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher Sun SITE Central Europe / RWTH Aachen University en
dc.relation.ispartof 24th Irish Conference on Artificial Intelligence and Cognitive Science 2016
dc.relation.uri http://ceur-ws.org/Vol-1751/
dc.rights © 2016, David Browne, Carlo Manna and Steven Prestwich. en
dc.rights.uri http://ceur-ws.org/ en
dc.subject Feature selection en
dc.subject Machine learning en
dc.subject Filter-based en
dc.subject Relevance-Redundancy Dominance en
dc.title Relevance-Redundancy Dominance: a threshold-free approach to filter-based feature selection en
dc.type Conference item en
dc.internal.authorcontactother Carlo Manna, Computer Science, University College Cork, Cork, Ireland. +353-21-490-3000 Email: c.manna@ucc.ie en
dc.internal.availability Full text available en
dc.date.updated 2017-08-15T10:25:30Z
dc.description.version Published Version en
dc.internal.rssid 407084825
dc.contributor.funder Science Foundation Ireland en
dc.description.status Peer reviewed en
dc.identifier.journaltitle CEUR Workshop Proceedings en
dc.internal.copyrightchecked Yes en
dc.internal.licenseacceptance Yes en
dc.internal.conferencelocation Dublin, Ireland en
dc.internal.IRISemailaddress c.manna@ucc.ie en
dc.internal.IRISemailaddress david.browne@insight-centre.org


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