Show simple item record Cornelis, Chris Jensen, Richard 2011-09-07T08:57:31Z 2011-09-07T08:57:31Z 2011-09-07
dc.identifier.citation Cornelis , C & Jensen , R 2011 , ' Fuzzy-Rough Nearest Neighbour Classification and Prediction ' Theoretical Computer Science , vol 412 , no. 42 , pp. 5871-5884 . DOI: 10.1016/j.tcs.2011.05.040 en
dc.identifier.issn 0304-3975
dc.identifier.other PURE: 170507
dc.identifier.other PURE UUID: 3d226423-77db-402e-86b5-2daa84ca1ed2
dc.identifier.other dspace: 2160/7564
dc.identifier.other DSpace_20121128.csv: row: 4441
dc.identifier.other RAD: 10559
dc.identifier.other RAD_Outputs_All_ID_Import_20121105.csv: row: 3766
dc.identifier.other Scopus: 80052812410
dc.description R. Jensen and C. Cornelis. Fuzzy-Rough Nearest Neighbour Classification and Prediction. Theoretical Computer Science, vol. 412, no. 42, pp. 5871-5884, 2011. en
dc.description.abstract Nearest neighbour (NN) approaches are inspired by the way humans make decisions, comparing a test object to previously encountered samples. In this paper, we propose an NN algorithm that uses the lower and upper approximations from fuzzy-rough set theory in order to classify test objects, or predict their decision value. It is shown experimentally that our method outperforms other NN approaches (classical, fuzzy and fuzzy-rough ones) and that it is competitive with leading classification and prediction methods. Moreover, we show that the robustness of our methods against noise can be enhanced effectively by invoking the approximations of the Vaguely Quantified Rough Set (VQRS) model, which emulates the linguistic quantifiers “some” and “most” from natural language. en
dc.format.extent 14 en
dc.language.iso eng
dc.relation.ispartof Theoretical Computer Science en
dc.rights en
dc.title Fuzzy-Rough Nearest Neighbour Classification and Prediction en
dc.type /dk/atira/pure/researchoutput/researchoutputtypes/contributiontojournal/article en
dc.contributor.institution Department of Computer Science en
dc.contributor.institution Advanced Reasoning Group en
dc.description.status Peer reviewed en

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