Assessing Potentiality of Support Vector Machine Method in Crude Oil Price Forecasting
Author:
Publisher
Modestum Publishing Ltd
Subject
Applied Mathematics,Education
Link
https://www.ejmste.com/download/assessing-potentiality-of-support-vector-machine-method-in-crude-oil-price-forecasting-5175.pdf
Reference42 articles.
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2. Burges, C. J. C. (1998). A tutorial on support vector machines for pattern recognition. Data Mining and Knowledge Discovery, 2, 121-167.
3. Cao, L. J., & Tay, F. E. H. (2001). Financial forecasting using support vector machines. Neural Computing Applications, 10, 184-192.
4. Cristianini, N., & Taylor, J. S. (2000). An Introduction to Support Vector Machines and Other Kernel-based Learning Methods. Cambridge University Press, New York.
5. Chou, J. R. (2016). An Empirical Study of User Experience on Touch Mice. Eurasia Journal of Mathematics, Science & Technology Education, 12(11), 2875-2885.
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