Comparative Analysis of Selected Supervised Classification Algorithms.

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dc.contributor.authorMabayoje, Modinat Abolore
dc.contributor.authorBalogun, Abdullateef Oluwagbemiga
dc.contributor.authorSalihu, Shakirat Aderonke
dc.contributor.authorOladipupo, Kehinde Razak
dc.date.accessioned2018-05-10T13:38:18Z
dc.date.available2018-05-10T13:38:18Z
dc.date.issued2015-10
dc.description.abstractInformation is not packaged in a standard easy-to-retrieve format. It is an underlying and usually subtle and misleading concept buried in massive amounts of raw data. From the beginning of time it has been man’s common goal to make his life easier. The prevailing notion in society is that wealth brings comfort and luxury, so it is not surprising that there has been so much work done on ways to sort large volume of data. Over the year, there are various data mining techniques and used to sort large volume of data. This paper considers Classification which is a supervised learning technique. Therefore the need to come up with the most efficient way to deal with voluminous data with very little time frame has been one of the biggest challenges to the AI community. Hence, this paper presents a comparative analysis of three classification algorithms namely; Decision Tree (J-48), Random Forest and Naïve Bayes. A 10-fold cross validation technique is used for the performance evaluation of the classifiers on KDD’’99, VOTE and CREDIT datasets using WEKA (Waikato Environment forKnowledge Analysis) tool. The experiment shows that the type of dataset determines which classifier is suitable.en_US
dc.identifier.citation17. Mabayoje, M. A., Balogun, A. O., Salihu, S. A., & Oladipupo, K. R. (2015): Comparative Analysis of Selected Supervised Classification Algorithms. African Journal of Computing & ICTs. 8(3); 35-42en_US
dc.identifier.issn2006-1781
dc.identifier.otherhttps://static.secure.website/wscfus/5655211/3185735/v8n3-2p7-2015-ajocict-comparative-analysis-of-selected-supervised-classification-algorithms.pdf
dc.identifier.urihttp://hdl.handle.net/123456789/230
dc.language.isoenen_US
dc.publisherComputer Chapter of the Institute of Electrical & Electronics Engineers (IEEE) Nigeria Section.en_US
dc.relation.ispartofseriesVolume: 8;Issue: 3
dc.subjectMachine Learningen_US
dc.subjectData Miningen_US
dc.subjectKnowledge Discoveryen_US
dc.titleComparative Analysis of Selected Supervised Classification Algorithms.en_US
dc.typeArticleen_US

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