Binary Genetic Swarm Optimization: A Combination of GA and PSO for Feature Selection

Binary Genetic Swarm Optimization: A Combination of GA and PSO for Feature Selection

Feature selection (FS) is a technique which helps to find the most optimal feature subset to develop an efficient pattern recognition model under consideration. The use of genetic algorithm (GA) and particle swarm optimization (PSO) in the field of FS is profound. In this paper, we propose an insigh...

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Bibliographic Details
Main Authors: Ghosh Manosij, Guha Ritam, Alam Imran, Lohariwal Priyank, Jalan Devesh, Sarkar Ram
Format: Article
Language:English
Published: De Gruyter 2019-09-01
Series:Journal of Intelligent Systems
Subjects:
feature selection
binary genetic swarm optimization
genetic algorithm
particle swarm optimization
uci dataset
average weighted combination
sequential one-point flipping
68t10
Online Access:https://doi.org/10.1515/jisys-2019-0062

Internet

https://doi.org/10.1515/jisys-2019-0062

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