A new gradient method for solving linear regression model

One of the commonly used optimization methods is the conjugate gradient (CG) method. This method is highly practical for solving large scale problems and applicable for real life. This study suggests another CG method that fulfills the sufficient descent and global convergence properties. The robust...

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Bibliographic Details
Published in:International Journal of Recent Technology and Engineering
Main Author: Zull N.; Aini N.; Rivaie M.; Mamat M.
Format: Article
Language:English
Published: Blue Eyes Intelligence Engineering and Sciences Publication 2019
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070258917&partnerID=40&md5=49ef2f681677be149d4f380491db5f76
id 2-s2.0-85070258917
spelling 2-s2.0-85070258917
Zull N.; Aini N.; Rivaie M.; Mamat M.
A new gradient method for solving linear regression model
2019
International Journal of Recent Technology and Engineering
7
5

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070258917&partnerID=40&md5=49ef2f681677be149d4f380491db5f76
One of the commonly used optimization methods is the conjugate gradient (CG) method. This method is highly practical for solving large scale problems and applicable for real life. This study suggests another CG method that fulfills the sufficient descent and global convergence properties. The robustness and efficiency of the proposed method are evaluated by comparison with other established CG methods. The numerical testing uses sixteen test functions in MATLAB subroutine programming under strong Wolfe line search. Numerically, the result concludes that the new CG method has the best performance in term of iteration number (NOI) and CPU time. This method is then implemented for solving linear regression model in order to show its applicability. Hence, this method has been proven to be successful. © BEIESP.
Blue Eyes Intelligence Engineering and Sciences Publication
22773878
English
Article

author Zull N.; Aini N.; Rivaie M.; Mamat M.
spellingShingle Zull N.; Aini N.; Rivaie M.; Mamat M.
A new gradient method for solving linear regression model
author_facet Zull N.; Aini N.; Rivaie M.; Mamat M.
author_sort Zull N.; Aini N.; Rivaie M.; Mamat M.
title A new gradient method for solving linear regression model
title_short A new gradient method for solving linear regression model
title_full A new gradient method for solving linear regression model
title_fullStr A new gradient method for solving linear regression model
title_full_unstemmed A new gradient method for solving linear regression model
title_sort A new gradient method for solving linear regression model
publishDate 2019
container_title International Journal of Recent Technology and Engineering
container_volume 7
container_issue 5
doi_str_mv
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070258917&partnerID=40&md5=49ef2f681677be149d4f380491db5f76
description One of the commonly used optimization methods is the conjugate gradient (CG) method. This method is highly practical for solving large scale problems and applicable for real life. This study suggests another CG method that fulfills the sufficient descent and global convergence properties. The robustness and efficiency of the proposed method are evaluated by comparison with other established CG methods. The numerical testing uses sixteen test functions in MATLAB subroutine programming under strong Wolfe line search. Numerically, the result concludes that the new CG method has the best performance in term of iteration number (NOI) and CPU time. This method is then implemented for solving linear regression model in order to show its applicability. Hence, this method has been proven to be successful. © BEIESP.
publisher Blue Eyes Intelligence Engineering and Sciences Publication
issn 22773878
language English
format Article
accesstype
record_format scopus
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