Kernel functions for the support vector machine: comparing performances on crude oil price data

The purpose of this research is to broaden the theoretic understanding of the effects of kernel functions for the support vector machine on crude oil price data. The performances of five (5) kernel functions of the support vector machine were compared. The analysis of variance was used for validatin...

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Main Authors:	Chiroma, Haruna, Abdulkareem, Sameem, Abubakar, Adamu, Herawan, Tutut
Format:	Book Chapter
Language:	English English
Published:	Springer International Publishing 2014
Subjects:	TP670 Oils, fats, waxes
Online Access:	http://irep.iium.edu.my/37928/ http://irep.iium.edu.my/37928/ http://irep.iium.edu.my/37928/ http://irep.iium.edu.my/37928/1/Kernel_Functions_for_the_Support_Vector_Machine_Comparing_Performances_on_Crude_Oil_Price_Data.pdf http://irep.iium.edu.my/37928/4/37928_Kernel%20functions%20for%20the%20support%20vector%20machine_SCOPUS.pdf

id	iium-37928
recordtype	eprints
spelling	iium-379282017-09-06T01:44:59Z http://irep.iium.edu.my/37928/ Kernel functions for the support vector machine: comparing performances on crude oil price data Chiroma, Haruna Abdulkareem, Sameem Abubakar, Adamu Herawan, Tutut TP670 Oils, fats, waxes The purpose of this research is to broaden the theoretic understanding of the effects of kernel functions for the support vector machine on crude oil price data. The performances of five (5) kernel functions of the support vector machine were compared. The analysis of variance was used for validating the results and we take additional steps to study the Post Hoc. Findings emanated from the research indicated that the performance of the wave kernel function was statistically significantly better than the radial basis function, polynomial, exponential, and sigmoid kernel functions. Computational efficiency of the wave activation function was poor compared with the other kernel functions in the study. This research could provide a better understanding of the behavior of the kernel functions for support vector machine on the crude oil price dataset. The study has the potentials of triggering interested researchers to propose a novel methodology that can advaced crude oil prediction accuracy. Springer International Publishing 2014-06 Book Chapter PeerReviewed application/pdf en http://irep.iium.edu.my/37928/1/Kernel_Functions_for_the_Support_Vector_Machine_Comparing_Performances_on_Crude_Oil_Price_Data.pdf application/pdf en http://irep.iium.edu.my/37928/4/37928_Kernel%20functions%20for%20the%20support%20vector%20machine_SCOPUS.pdf Chiroma, Haruna and Abdulkareem, Sameem and Abubakar, Adamu and Herawan, Tutut (2014) Kernel functions for the support vector machine: comparing performances on crude oil price data. In: Recent advances on soft computing and data mining: proceedings of The First International Conference on Soft Computing and Data Mining (SCDM-2014) Universiti Tun Hussein Onn Malaysia, Johor, MalaysiaJune 16th-18th, 2014. Advances in Intelligent Systems and Computing, 287 . Springer International Publishing, London, pp. 273-281. ISBN 9783319076911 http://link.springer.com/chapter/10.1007%2F978-3-319-07692-8_26 10.1007/978-3-319-07692-8_26
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	TP670 Oils, fats, waxes
spellingShingle	TP670 Oils, fats, waxes Chiroma, Haruna Abdulkareem, Sameem Abubakar, Adamu Herawan, Tutut Kernel functions for the support vector machine: comparing performances on crude oil price data
description	The purpose of this research is to broaden the theoretic understanding of the effects of kernel functions for the support vector machine on crude oil price data. The performances of five (5) kernel functions of the support vector machine were compared. The analysis of variance was used for validating the results and we take additional steps to study the Post Hoc. Findings emanated from the research indicated that the performance of the wave kernel function was statistically significantly better than the radial basis function, polynomial, exponential, and sigmoid kernel functions. Computational efficiency of the wave activation function was poor compared with the other kernel functions in the study. This research could provide a better understanding of the behavior of the kernel functions for support vector machine on the crude oil price dataset. The study has the potentials of triggering interested researchers to propose a novel methodology that can advaced crude oil prediction accuracy.
format	Book Chapter
author	Chiroma, Haruna Abdulkareem, Sameem Abubakar, Adamu Herawan, Tutut
author_facet	Chiroma, Haruna Abdulkareem, Sameem Abubakar, Adamu Herawan, Tutut
author_sort	Chiroma, Haruna
title	Kernel functions for the support vector machine: comparing performances on crude oil price data
title_short	Kernel functions for the support vector machine: comparing performances on crude oil price data
title_full	Kernel functions for the support vector machine: comparing performances on crude oil price data
title_fullStr	Kernel functions for the support vector machine: comparing performances on crude oil price data
title_full_unstemmed	Kernel functions for the support vector machine: comparing performances on crude oil price data
title_sort	kernel functions for the support vector machine: comparing performances on crude oil price data
publisher	Springer International Publishing
publishDate	2014
url	http://irep.iium.edu.my/37928/ http://irep.iium.edu.my/37928/ http://irep.iium.edu.my/37928/ http://irep.iium.edu.my/37928/1/Kernel_Functions_for_the_Support_Vector_Machine_Comparing_Performances_on_Crude_Oil_Price_Data.pdf http://irep.iium.edu.my/37928/4/37928_Kernel%20functions%20for%20the%20support%20vector%20machine_SCOPUS.pdf
first_indexed	2023-09-18T20:54:23Z
last_indexed	2023-09-18T20:54:23Z
_version_	1777410206657937408

Kernel functions for the support vector machine: comparing performances on crude oil price data

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