Differential Evolution Based Nearest Prototype Classifier with Optimized Distance Measures and GOWA

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dc.contributor.authorKoloseni, David
dc.contributor.authorLuukka, Pasi
dc.date.accessioned2016-09-21T17:24:39Z
dc.date.available2016-09-21T17:24:39Z
dc.date.issued2015
dc.descriptionFull text can be accessed at http://link.springer.com/chapter/10.1007/978-3-319-11313-5_66en_US
dc.description.abstractNearest prototype classifier based on differential evolution algorithm, pool of distances and generalized ordered weighted averaging is introduced. Classifier is based on forming optimal ideal solutions for each class. Besides this also distance measures are optimized for each feature in the data sets to improve recognition process of which class the sample belongs. This leads to a distance vectors, which are now aggregated to a single distance by using generalized weighted averaging (GOWA). In earlier work simple sum was applied in the aggregation process. The classifier is empirically tested with seven data sets. The proposed classifier provided at least comparable accuracy or outperformed the compared classifiers, including the earlier versions of DE classifier and DE classifier with pool of distances.en_US
dc.identifier.citationKoloseni, D. and Luukka, P., 2015. Differential Evolution Based Nearest Prototype Classifier with Optimized Distance Measures and GOWA. In Intelligent Systems' 2014 (pp. 753-763). Springer International Publishing.en_US
dc.identifier.doi10.1007/978-3-319-11313-5_66
dc.identifier.urihttp://hdl.handle.net/20.500.11810/4179
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.subjectClassificationen_US
dc.subjectDifferential evolutionen_US
dc.subjectPool of distancesen_US
dc.subjectGeneralized ordered weighted averaging operatoren_US
dc.titleDifferential Evolution Based Nearest Prototype Classifier with Optimized Distance Measures and GOWAen_US
dc.typeBook chapteren_US
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