Improvement in the learning process as a function of distribution characteristics of binary data set

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dc.contributor.authorAltun Halis
dc.contributor.authorYalcinoz Tankut
dc.contributor.authorTezekici Bekir Sami
dc.date.accessioned2019-08-01T13:38:39Z
dc.date.available2019-08-01T13:38:39Z
dc.date.issued2000
dc.departmentNiğde ÖHÜ
dc.descriptionIEEE
dc.description10th Mediterranean Electrotechnical Conference (MALECON2000) -- 29 May 2000 through 31 May 2000 -- Lemesos, Cyprus -- 57862
dc.description.abstractIn literature improvements in neural learning are reported on, which have been achieved through input data manipulation, based on entirely experimental studies. Theoretical background is not supplied for these studies and neural networks are employed as a 'black box' model. Within this work, this problem is highlighted and the impact of the modified training sets is evaluated in order to establish a theoretical background for the phenomenon. For this end, a number of binary training data is employed to show how does the learning process depend on data distribution within the training sets.
dc.identifier.endpage569
dc.identifier.scopus2-s2.0-0034484211
dc.identifier.scopusqualityN/A
dc.identifier.startpage567
dc.identifier.urihttps://hdl.handle.net/11480/1391
dc.identifier.volume2
dc.identifier.wosWOS:000166106500138
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthor[0-Belirlenecek]
dc.language.isoen
dc.publisherIEEE, Piscataway, NJ, United States
dc.relation.ispartofProceedings of the Mediterranean Electrotechnical Conference - MELECON
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.titleImprovement in the learning process as a function of distribution characteristics of binary data set
dc.typeConference Object

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