Please use this identifier to cite or link to this item: http://ir.futminna.edu.ng:8080/jspui/handle/123456789/13619
Title: A Conceptual Nigeria Stock Exchange Prediction: Implementation Using Support Vector Machines-SMO Model
Authors: Abubakar, S. Magaji
Audu, Isah
Victor, Onomza Waziri
Adeboye, K.R.
Keywords: Nigerian Stock Market
Machine
Support Vector
Prediction
Data Mining
Machine Learning
Issue Date: 2013
Publisher: World of Computer Science and Information Technology Journal (WCSIT)
Series/Report no.: volume 3, No. 4;85-90
Abstract: This 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.
URI: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/13619
ISSN: 2221-0741
Appears in Collections:Statistics



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