Improved classifier chain methods based on heuristic optimization techniques for multi-label classification problem

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

Saved in:
書目詳細資料
主要作者: Oyekunle, Adeleke Abdullahi
格式: Thesis
語言:English
English
English
出版: 2022
主題:
在線閱讀:http://eprints.uthm.edu.my/8378/1/24p%20ADELEKE%20ABDULLAHI%20OYEKUNLE.pdf
http://eprints.uthm.edu.my/8378/2/ADELEKE%20ABDULLAHI%20OYEKUNLE%20COPYRIGHT%20DECLARATION.pdf
http://eprints.uthm.edu.my/8378/3/ADELEKE%20ABDULLAHI%20OYEKUNLE%20WATERMARK.pdf
標簽: 添加標簽
沒有標簽, 成為第一個標記此記錄!
id my-uthm-ep.8378
record_format uketd_dc
spelling my-uthm-ep.83782023-02-23T06:29:05Z Improved classifier chain methods based on heuristic optimization techniques for multi-label classification problem 2022-09 Oyekunle, Adeleke Abdullahi TS155-194 Production management. Operations management 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 2022-09 Thesis http://eprints.uthm.edu.my/8378/ http://eprints.uthm.edu.my/8378/1/24p%20ADELEKE%20ABDULLAHI%20OYEKUNLE.pdf text en public http://eprints.uthm.edu.my/8378/2/ADELEKE%20ABDULLAHI%20OYEKUNLE%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/8378/3/ADELEKE%20ABDULLAHI%20OYEKUNLE%20WATERMARK.pdf text en validuser phd doctoral Universiti Tun Hussein Onn Malaysia Fakulti Sains Komputer dan Sistem Maklumat
institution Universiti Tun Hussein Onn Malaysia
collection UTHM Institutional Repository
language English
English
English
topic TS155-194 Production management
Operations management
spellingShingle TS155-194 Production management
Operations management
Oyekunle, Adeleke Abdullahi
Improved classifier chain methods based on heuristic optimization techniques for multi-label classification problem
description 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
format Thesis
qualification_name Doctor of Philosophy (PhD.)
qualification_level Doctorate
author Oyekunle, Adeleke Abdullahi
author_facet Oyekunle, Adeleke Abdullahi
author_sort Oyekunle, Adeleke Abdullahi
title Improved classifier chain methods based on heuristic optimization techniques for multi-label classification problem
title_short Improved classifier chain methods based on heuristic optimization techniques for multi-label classification problem
title_full Improved classifier chain methods based on heuristic optimization techniques for multi-label classification problem
title_fullStr Improved classifier chain methods based on heuristic optimization techniques for multi-label classification problem
title_full_unstemmed Improved classifier chain methods based on heuristic optimization techniques for multi-label classification problem
title_sort improved classifier chain methods based on heuristic optimization techniques for multi-label classification problem
granting_institution Universiti Tun Hussein Onn Malaysia
granting_department Fakulti Sains Komputer dan Sistem Maklumat
publishDate 2022
url http://eprints.uthm.edu.my/8378/1/24p%20ADELEKE%20ABDULLAHI%20OYEKUNLE.pdf
http://eprints.uthm.edu.my/8378/2/ADELEKE%20ABDULLAHI%20OYEKUNLE%20COPYRIGHT%20DECLARATION.pdf
http://eprints.uthm.edu.my/8378/3/ADELEKE%20ABDULLAHI%20OYEKUNLE%20WATERMARK.pdf
_version_ 1776103331672883200