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...
Published in: | International Journal of Recent Technology and Engineering |
---|---|
Main Author: | |
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 |
collection |
Scopus |
_version_ |
1809677905392828416 |