Differential Evolution Classifier with Optimized OWA-Based Multi-distance Measures for the Features in the Data Sets

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dc.creatorKoloseni, David
dc.creatorFedrizzi, Mario
dc.creatorLuukka, Pasi
dc.creatorLampinen, Jouni
dc.creatorCollan, Mikael
dc.date2016-09-21T14:26:02Z
dc.date2016-09-21T14:26:02Z
dc.date2015
dc.date.accessioned2018-03-27T08:58:14Z
dc.date.available2018-03-27T08:58:14Z
dc.descriptionFull text can be accessed at http://link.springer.com/chapter/10.1007/978-3-319-11313-5_67
dc.descriptionThis paper introduces a new classification method that uses the differential evolution algorithm to feature-wise select, from a pool of distance measures, an optimal distance measure to be used for classification of elements. The distances yielded for each feature by the optimized distance measures are aggregated into an overall distance vector for each element by using OWA based multi-distance aggregation.
dc.identifierKoloseni, D., Fedrizzi, M., Luukka, P., Lampinen, J. and Collan, M., 2015. Differential Evolution Classifier with Optimized OWA-Based Multi-distance Measures for the Features in the Data Sets. In Intelligent Systems' 2014 (pp. 765-777). Springer International Publishing.
dc.identifierhttp://hdl.handle.net/20.500.11810/4039
dc.identifier10.1007/978-3-319-11313-5_67
dc.identifier.urihttp://hdl.handle.net/20.500.11810/4039
dc.languageen
dc.publisherSpringer
dc.subjectClassification
dc.subjectDifferential evolution
dc.subjectPool of distances
dc.subjectMulti-distances
dc.titleDifferential Evolution Classifier with Optimized OWA-Based Multi-distance Measures for the Features in the Data Sets
dc.typeBook chapter

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