Please use this identifier to cite or link to this item: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/13619
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dc.contributor.authorAbubakar, S. Magaji-
dc.contributor.authorAudu, Isah-
dc.contributor.authorVictor, Onomza Waziri-
dc.contributor.authorAdeboye, K.R.-
dc.date.accessioned2021-08-18T10:06:42Z-
dc.date.available2021-08-18T10:06:42Z-
dc.date.issued2013-
dc.identifier.issn2221-0741-
dc.identifier.urihttp://repository.futminna.edu.ng:8080/jspui/handle/123456789/13619-
dc.description.abstractThis paper is a continuation of our research work on the Nigerian Stock Exchange (NSE) market uncertainties, In our first paper (Magaji et al, 2013) we presented the Naive Bayes algorithm as a tool for predicting the Nigerian Stock Exchange Market; subsequently we used the same transformed data of the NSE and explored the implementation of the Support Vector Machine algorithm on the WEKA platform, and results obtained, made us to also conclude that the Support Vector Machine-SOM is another algorithm that provides an avenue for predicting the Nigerian Stock Exchange.en_US
dc.publisherWorld of Computer Science and Information Technology Journal (WCSIT)en_US
dc.relation.ispartofseriesvolume 3, No. 4;85-90-
dc.subjectNigerian Stock Marketen_US
dc.subjectMachineen_US
dc.subjectSupport Vectoren_US
dc.subjectPredictionen_US
dc.subjectData Miningen_US
dc.subjectMachine Learningen_US
dc.titleA Conceptual Nigeria Stock Exchange Prediction: Implementation Using Support Vector Machines-SMO Modelen_US
dc.typeArticleen_US
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