Differential Evolution Based Classification with Pool of Distances and Aggregation Operators

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dc.contributor.authorKoloseni, David
dc.date.accessioned2016-09-21T17:24:52Z
dc.date.available2016-09-21T17:24:52Z
dc.date.issued2015
dc.description.abstractThe objective of this thesis is to develop and generalize further the differential evolution based data classification method. For many years, evolutionary algorithms have been successfully applied to many classification tasks. Evolution algorithms are population based, stochastic search algorithms that mimic natural selection and genetics. Differential evolution is an evolutionary algorithm that has gained popularity because of its simplicity and good observed performance. In this thesis a differential evolution classifier with pool of ...en_US
dc.identifier.citationKoloseni, D., 2015. Differential evolution based classification with pool of distances and aggregation operators. Acta Universitatis Lappeenrantaensis.en_US
dc.identifier.urihttp://hdl.handle.net/20.500.11810/4180
dc.language.isoenen_US
dc.publisherLappeenranta University of Technologyen_US
dc.titleDifferential Evolution Based Classification with Pool of Distances and Aggregation Operatorsen_US
dc.typeJournal Article, Peer Revieweden_US
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