Binary grey wolf optimizer with a novel population adaptation strategy for feature selection

Binary grey wolf optimizer with a novel population adaptation strategy for feature selection

Feature selection is a fundamental pre-processing step in machine learning that aims to reduce the dimensionality of a dataset by selecting the most effective features from the original features. This process is regarded as a combinatorial optimization problem, and the grey wolf optimizer (GWO), a n...

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Bibliographic Details
Main Authors: Huang, M. (Author), Ji, Y. (Author), Wang, D. (Author), Wang, H. (Author)
Format: Article
Language:English
Published: John Wiley and Sons Inc 2023
Subjects:
Adaptation strategies
classification
Classification (of information)
Combinatorial optimization
Combinatorial optimization problems
dynamic mutation
Dynamic mutation
feature selection
Feature Selection
Features selection
Gray wolf optimizer
Gray wolves
grey wolf optimizer
Heuristic algorithms
Machine-learning
Optimizers
population adaptation strategy
Population adaptation strategy
Pre-processing step
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