Binary Text Classification Using An Ensemble of Naïve Bayes and Support Vector Machines

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dc.contributor.authorAbikoye, Oluwakemi Christiana
dc.contributor.authorOmokanye, Samuel Oladeji
dc.contributor.authorAro, Taye Oladele
dc.date.accessioned2018-03-21T10:13:26Z
dc.date.available2018-03-21T10:13:26Z
dc.date.issued2017
dc.description.abstractText classification is being done by classifiers over the years, combining classifiers together can result in better classification and thus Naïve Bayes algorithm is combined with Support vector machine through stacking and the results shows that the ensemble results in an increase in the classification accuracy though at the expense of the time taken by the ensemble to build its classification modelen_US
dc.identifier.citationAbikoye, Oluwakemi Christiana, Omokanye, Samuel Oladeji. & Aro, Taye Oladele. (2017): Binary Text Classification Using An Ensemble of Naïve Bayes and Support Vector Machines .GESJ:Computer Sciences and Telecommunications. 2(52); 37-45, Published by Internet Academy, Georgiaen_US
dc.identifier.urihttp://gesj.internet-academy.org.ge/download.php?id=3011.pdf
dc.identifier.urihttp://hdl.handle.net/123456789/139
dc.language.isoenen_US
dc.publisherGeorgian Technical University and St. Andrew the First Called Georgian University of The Patriarchy of Georgiaen_US
dc.subjectNaïve Bayesen_US
dc.subjectSupport vector machineen_US
dc.subjecttext classificationen_US
dc.subjectensembleen_US
dc.subjectBinaryen_US
dc.titleBinary Text Classification Using An Ensemble of Naïve Bayes and Support Vector Machinesen_US
dc.typeArticleen_US

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