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dc.contributor.author Jensen, Richard
dc.contributor.author Cornelis, Chris
dc.date.accessioned 2010-11-12T09:28:26Z
dc.date.available 2010-11-12T09:28:26Z
dc.date.issued 2010-11-12
dc.identifier.citation Jensen , R & Cornelis , C 2010 , ' A New Approach to Fuzzy-Rough Nearest Neighbour Classification ' Transactions on Rough Sets XIII , pp. 56-72 . en
dc.identifier.other PURE: 161777
dc.identifier.other dspace: 2160/5866
dc.identifier.uri http://hdl.handle.net/2160/5866
dc.description R. Jensen and C. Cornelis. A New Approach to Fuzzy-Rough Nearest Neighbour Classification. Transactions on Rough Sets XIII, LNCS 6499, pp. 56-72, 2011. en
dc.description.abstract A new fuzzy-rough nearest neighbour (FRNN) classification algorithm is presented in this paper, as an alternative to Sarkar¿s fuzzy-rough ownership function (FRNN-O) approach. By contrast to the latter, our method uses the nearest neighbours to construct lower and upper approximations of decision classes, and classifies test instances based on their membership to these approximations. In the experimental analysis, we evaluate our approach with both classical fuzzy-rough approximations (based on an implicator and a t-norm), as well as with the recently introduced vaguely quantified rough sets. Preliminary results are very good, and in general FRNN outperforms FRNN-O, as well as the traditional fuzzy nearest neighbour (FNN) algorithm. en
dc.format.extent 17 en
dc.language.iso eng
dc.relation.ispartof Transactions on Rough Sets XIII en
dc.title A New Approach to Fuzzy-Rough Nearest Neighbour Classification en
dc.type Text en
dc.type.publicationtype Article (Journal) en
dc.contributor.institution Department of Computer Science en
dc.description.status Peer reviewed en


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