Particle Swarm Optimization for Feature Selection: A Review of Filter-based Classification to Identify Challenges and Opportunities

Marianne Cherrington, David Airehrour, Joan Lu, Fadi Thabtah, Qiang Xu, Samaneh Madanian

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Feature selection (FS) is a fundamental big data task, improving classification performance by selecting a relevant feature subset to mitigate the 'curse of dimensionality'. As the number of attributes increase, search algorithms can limit FS methods. Particle swarm optimization (PSO) is a global search metaheuristic, with the ability to search a space of large dimension quickly, with few assumptions. This review explores filter FS classification methods that exploit contemporary particle swarm optimization research, categorizing state-of-the-art techniques. The major contribution of this review is in highlighting the uses and limitations of these currently underrepresented techniques, to identify current challenges and opportunities, so further productive research may be exploited.

Original languageEnglish
Title of host publication 2019 IEEE 10th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)
EditorsSatyajit Chakrabarti, Himadri Nath Saha
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages523-529
Number of pages7
ISBN (Electronic)9781728125305
ISBN (Print)9781728125312
DOIs
Publication statusPublished - 19 Dec 2019
Event10th IEEE Annual Information Technology, Electronics and Mobile Communication Conference - Vancouver, Canada
Duration: 17 Oct 201919 Oct 2019
Conference number: 10
http://ieee-iemcon.org/

Conference

Conference10th IEEE Annual Information Technology, Electronics and Mobile Communication Conference
Abbreviated titleIEMCON 2019
CountryCanada
CityVancouver
Period17/10/1919/10/19
Internet address

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    Cherrington, M., Airehrour, D., Lu, J., Thabtah, F., Xu, Q., & Madanian, S. (2019). Particle Swarm Optimization for Feature Selection: A Review of Filter-based Classification to Identify Challenges and Opportunities. In S. Chakrabarti, & H. N. Saha (Eds.), 2019 IEEE 10th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) (pp. 523-529). [8936185] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IEMCON.2019.8936185