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A Conceptual Nigeria Stock Exchange Prediction: Implementation Using Support Vector Machines-SMO Model

Author(s): Abubakar S. Magaji | Victor Onomza Waziri | Audu Isah | Adeboye K.R.

Journal: World of Computer Science and Information Technology Journal
ISSN 2221-0741

Volume: 3;
Issue: 4;
Start page: 85;
Date: 2013;
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Keywords: Nigerian Stock Market | Prediction | Data Mining | Machine Learning | Support Vector Machine.

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.
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