Genetic algorithm feature selection resilient to increasing amounts of data imputation
This paper investigates the robustness of a genetic algorithm (GA) in feature selection across a dataset with increasing imputed missing values. Feature selection can be beneficial in predictive modeling to reduce computational costs and potentially improve performance. Beyond these benefits, it al...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
LibraryPress@UF
2024-05-01
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| Series: | Proceedings of the International Florida Artificial Intelligence Research Society Conference |
| Subjects: | |
| Online Access: | https://journals.flvc.org/FLAIRS/article/view/135723 |
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