Associative classification in multi-label classification : an investigative study
Joint Authors
al-Ziyadah, Raid
al-Maiah, Muhammad Amin
al-Luwaici, Muadh
Source
Jordanian Journal of Computetrs and Information Technology
Issue
Vol. 7, Issue 2 (30 Jun. 2021), pp.166-179, 14 p.
Publisher
Princess Sumaya University for Technology
Publication Date
2021-06-30
Country of Publication
Jordan
No. of Pages
14
Main Subjects
Information Technology and Computer Science
Abstract EN
Multi-label classification (MLC) is a very interesting and important domain that has attracted many researchers in the last two decades.
Several single-label classification algorithms that belong to different learning strategies have been adapted to handle the problem of MLC.
Surprisingly, no Associative Classification (AC) algorithm has been adapted to handle the MLC problem, where AC algorithms have shown a high predictive performance compared with other learning strategies in single-label classification.
In this paper, a deep investigation regarding utilizing AC in MLC is presented.
An evaluation of several AC algorithms on three multi-label datasets with respect to five discretization techniques revealed that utilizing AC algorithms in MLC is very promising compared with other algorithms from different learning strategies.
American Psychological Association (APA)
al-Ziyadah, Raid& al-Maiah, Muhammad Amin& al-Luwaici, Muadh. 2021. Associative classification in multi-label classification : an investigative study. Jordanian Journal of Computetrs and Information Technology،Vol. 7, no. 2, pp.166-179.
https://search.emarefa.net/detail/BIM-1415802
Modern Language Association (MLA)
al-Ziyadah, Raid…[et al.]. Associative classification in multi-label classification : an investigative study. Jordanian Journal of Computetrs and Information Technology Vol. 7, no. 2 (Jun. 2021), pp.166-179.
https://search.emarefa.net/detail/BIM-1415802
American Medical Association (AMA)
al-Ziyadah, Raid& al-Maiah, Muhammad Amin& al-Luwaici, Muadh. Associative classification in multi-label classification : an investigative study. Jordanian Journal of Computetrs and Information Technology. 2021. Vol. 7, no. 2, pp.166-179.
https://search.emarefa.net/detail/BIM-1415802
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 176-179
Record ID
BIM-1415802