View source for Publications:Learning an Adaptive Dissimilarity Measure for Nearest Neighbour Classification

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{{PublicationSetupTemplate|Author=Antanas Verikas, M. Bacauskiene, Kerstin Malmqvist
|PID=237389
|Name=Verikas, Antanas (av) (0000-0003-2185-8973) (Högskolan i Halmstad (2804), Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) (3905), Halmstad Embedded and Intelligent Systems Research (EIS) (3938), Intelligenta system (IS-lab) (3941));Bacauskiene, M. (Department of Applied Electronics, Kaunas University of Technology Kaunas, Lithuania);Malmqvist, Kerstin (Högskolan i Halmstad (2804), Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) (3905), Halmstad Embedded and Intelligent Systems Research (EIS) (3938), Intelligenta system (IS-lab) (3941))
|Title=Learning an Adaptive Dissimilarity Measure for Nearest Neighbour Classification
|PublicationType=Journal Paper
|ContentType=Refereegranskat
|Language=eng
|Journal=Neural computing & applications (Print)
|JournalISSN=0941-0643
|Status=published
|Volume=11
|Issue=3-4
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|Conference=
|StartPage=203
|EndPage=209
|Year=2003
|Edition=
|Pages=
|City=London
|Publisher=Springer
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|DOI=http://dx.doi.org/10.1007/s00521-003-0356-1
|ISI=000184615000009
|PMID=
|ScopusId=2-s2.0-0038792231
|NBN=urn:nbn:se:hh:diva-211
|LocalId=2082/506
|ArchiveNumber=
|Keywords=Classification;Clustering;Learning vector quantisation;Nearest neighbour;Neural network
|Categories=Data- och informationsvetenskap (102)
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|Abstract=<p>In this paper, an approach to weighting features for classification based on the nearest-neighbour rules is proposed. The weights are adaptive in the sense that the weight values are different in various regions of the feature space. The values of the weights are found by performing a random search in the weight space. A correct classification rate is the criterion maximised during the search. Experimentally, we have shown that the proposed approach is useful for classification. The weight values obtained during the experiments show that the importance of features may be different in different regions of the feature space</p>
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|CreatedDate=2006-11-24
|PublicationDate=2006-11-24
|LastUpdated=2014-11-10
|diva=http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:237389}}
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