The effect of kernel functions on cryptocurrency prediction using support vector machines

Hitam, Nor Azizah and Ismail, Amelia Ritahani and Samsudin, Ruhaidah and Alkhammash, Eman H. (2021) The effect of kernel functions on cryptocurrency prediction using support vector machines. In: 6th International Conference on Reliable Information and Communication Technology 2021, Virtual. (Unpublished)

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Abstract

Forecasting in the financial sector has proven to be a highly important area of study in the science of Computational Intelligence (CI). Furthermore, the availability of social media platforms contributes to the advancement of SVM re- search and the selection of SVM parameters. Using SVM kernel functions, this study examines the four kernel functions available: Linear, Radial Basis Gaussian (RBF), Polynomial, and Sigmoid kernels, for the purpose of cryptocurrency and foreign ex- change market prediction. The available technical numerical data, sentiment data, and a technical indicator were used in this experimental research, which was conducted in a controlled environment. The cost and epsilon-SVM regression techniques are both being utilised, and they are both being performed across the five datasets in this study. On the basis of three performance measures, which are the MAE, MSE, and RMSE, the results have been compared and assessed. The forecasting models developed in this research are used to predict all of the outcomes. The SVM-RBF kernel forecast- ing model, which has outperformed other SVM-kernel models in terms of error rate generated, are presented as a conclusion to this study.

Item Type:	Conference or Workshop Item (Plenary Papers)
Additional Information:	4296/95674
Uncontrolled Keywords:	Cryptocurrency, Computational Intelligence (CI), Support Vector Machine (SVM), Radial Basis Gaussian (RBF) kernel, Linear Kernel, Polyno- mial Kernel, Sigmoid Kernel
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology > Department of Computer Science
Depositing User:	Amelia Ritahani Ismail
Date Deposited:	12 Jan 2022 15:07
Last Modified:	12 Jan 2022 15:07
URI:	http://irep.iium.edu.my/id/eprint/95674

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