S-shaped vs. V-shaped transfer functions for ant lion optimization algorithm in feature selection problem

Majdi Mafarja, Derar Eleyan, Salwani Abdullah, Seyedali Mirjalili

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

12 Citations (Scopus)

Abstract

Feature selection is an important preprocessing step for classification problems. It deals with selecting near optimal features in the original dataset. Feature selection is an NP-hard problem, so meta-heuristics can be more efficient than exact methods. In this work, Ant Lion Optimizer (ALO), which is a recent metaheuristic algorithm, is employed as a wrapper feature selection method. Six variants of ALO are proposed where each employ a transfer function to map a continuous search space to a discrete search space. The performance of the proposed approaches is tested on eighteen UCI datasets and compared to a number of existing approaches in the literature: Particle Swarm Optimization, Gravitational Search Algorithm and two existing ALO-based approaches. Computational experiments show that the proposed approaches efficiently explore the feature space and select the most informative features, which help to improve the classification accuracy.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Future Networks and Distributed Systems, ICFNDS 2017
PublisherAssociation for Computing Machinery
VolumePart F130522
ISBN (Electronic)9781450348447
DOIs
Publication statusPublished - 19 Jul 2017
Externally publishedYes
Event2017 International Conference on Future Networks and Distributed Systems, ICFNDS 2017 - Cambridge, United Kingdom
Duration: 19 Jul 201720 Jul 2017

Other

Other2017 International Conference on Future Networks and Distributed Systems, ICFNDS 2017
CountryUnited Kingdom
CityCambridge
Period19/7/1720/7/17

Fingerprint

Transfer functions
Feature extraction
Particle swarm optimization (PSO)
Computational complexity
Experiments

Keywords

  • Antlion optimization algorithm
  • Classification
  • Feature selection
  • Optimization
  • Transfer functions

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

Cite this

Mafarja, M., Eleyan, D., Abdullah, S., & Mirjalili, S. (2017). S-shaped vs. V-shaped transfer functions for ant lion optimization algorithm in feature selection problem. In Proceedings of the International Conference on Future Networks and Distributed Systems, ICFNDS 2017 (Vol. Part F130522). [3102325] Association for Computing Machinery. https://doi.org/10.1145/3102304.3102325

S-shaped vs. V-shaped transfer functions for ant lion optimization algorithm in feature selection problem. / Mafarja, Majdi; Eleyan, Derar; Abdullah, Salwani; Mirjalili, Seyedali.

Proceedings of the International Conference on Future Networks and Distributed Systems, ICFNDS 2017. Vol. Part F130522 Association for Computing Machinery, 2017. 3102325.

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

Mafarja, M, Eleyan, D, Abdullah, S & Mirjalili, S 2017, S-shaped vs. V-shaped transfer functions for ant lion optimization algorithm in feature selection problem. in Proceedings of the International Conference on Future Networks and Distributed Systems, ICFNDS 2017. vol. Part F130522, 3102325, Association for Computing Machinery, 2017 International Conference on Future Networks and Distributed Systems, ICFNDS 2017, Cambridge, United Kingdom, 19/7/17. https://doi.org/10.1145/3102304.3102325
Mafarja M, Eleyan D, Abdullah S, Mirjalili S. S-shaped vs. V-shaped transfer functions for ant lion optimization algorithm in feature selection problem. In Proceedings of the International Conference on Future Networks and Distributed Systems, ICFNDS 2017. Vol. Part F130522. Association for Computing Machinery. 2017. 3102325 https://doi.org/10.1145/3102304.3102325
Mafarja, Majdi ; Eleyan, Derar ; Abdullah, Salwani ; Mirjalili, Seyedali. / S-shaped vs. V-shaped transfer functions for ant lion optimization algorithm in feature selection problem. Proceedings of the International Conference on Future Networks and Distributed Systems, ICFNDS 2017. Vol. Part F130522 Association for Computing Machinery, 2017.
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