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Dual heuristic feature selection based on genetic algorithm and binary particle swarm optimization
Joint Authors
Jabbur, Ali Hakim
Ali, Ali Husayn
Source
Journal of Babylon University : Journal of Applied and Pure Sciences
Issue
Vol. 27, Issue 1 (28 Feb. 2019), pp.171-183, 13 p.
Publisher
Publication Date
2019-02-28
Country of Publication
Iraq
No. of Pages
13
Main Subjects
Mathematics
Information Technology and Computer Science
Abstract EN
The features selection is one of the data mining tools that used to select the most important features of a given dataset.
It contributes to save time and memory during the handling a given dataset.
According to these principles, we have proposed features selection method based on mixing two metaheuristic algorithms Binary Particle Swarm Optimization and Genetic Algorithm work individually.
The K-Nearest Neighbour (K-NN) is used as an objective function to evaluate the proposed features selection algorithm.
The Dual Heuristic Feature Selection based on Genetic Algorithm and Binary Particle Swarm Optimization (DHFS) test, and compared with 26 well-known datasets of UCI machine learning.
The numeric experiments result imply that the DHFS better performance compared with full features and that selected by the mentioned algorithms (Genetic Algorithm and Binary Particle Swarm Optimization).
American Psychological Association (APA)
Jabbur, Ali Hakim& Ali, Ali Husayn. 2019. Dual heuristic feature selection based on genetic algorithm and binary particle swarm optimization. Journal of Babylon University : Journal of Applied and Pure Sciences،Vol. 27, no. 1, pp.171-183.
https://search.emarefa.net/detail/BIM-1094612
Modern Language Association (MLA)
Jabbur, Ali Hakim& Ali, Ali Husayn. Dual heuristic feature selection based on genetic algorithm and binary particle swarm optimization. Journal of Babylon University : Journal of Applied and Pure Sciences Vol. 27, no. 1 (2019), pp.171-183.
https://search.emarefa.net/detail/BIM-1094612
American Medical Association (AMA)
Jabbur, Ali Hakim& Ali, Ali Husayn. Dual heuristic feature selection based on genetic algorithm and binary particle swarm optimization. Journal of Babylon University : Journal of Applied and Pure Sciences. 2019. Vol. 27, no. 1, pp.171-183.
https://search.emarefa.net/detail/BIM-1094612
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 181-182
Record ID
BIM-1094612