Oyekunle, Adeleke Abdullahi (2022) Improved classifier chain methods based on heuristic optimization techniques for multi-label classification problem. Doctoral thesis, Universiti Tun Hussein Onn Malaysia.
|
Text
24p ADELEKE ABDULLAHI OYEKUNLE.pdf Download (735kB) | Preview |
|
![[img]](http://eprints.uthm.edu.my/style/images/fileicons/text.png) |
Text (Copyright Declaration)
ADELEKE ABDULLAHI OYEKUNLE COPYRIGHT DECLARATION.pdf Restricted to Repository staff only Download (809kB) | Request a copy |
|
|
Text (Full Text)
ADELEKE ABDULLAHI OYEKUNLE WATERMARK.pdf Restricted to Registered users only Download (30MB) | Request a copy |
Abstract
This thesis is about proposing multi-label classification (MLC) techniques for classification applications. In MLC, the task is to develop models that could predict multiple class labels
| Item Type: | Thesis (Doctoral) |
|---|---|
| Subjects: | T Technology > TS Manufactures > TS155-194 Production management. Operations management |
| Divisions: | Faculty of Computer Science and Information Technology > Department of Information Security |
| Depositing User: | Mrs. Sabarina Che Mat |
| Date Deposited: | 23 Feb 2023 06:29 |
| Last Modified: | 23 Feb 2023 06:29 |
| URI: | http://eprints.uthm.edu.my/id/eprint/8378 |
Actions (login required)
 |
View Item |