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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2401.10846 |
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| _version_ | 1866913200916660224 |
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| author | Potter, Michael Yıldız, Ayberk Yarkın Prabhu, Nishanth Marer Gordon, Cameron |
| author_facet | Potter, Michael Yıldız, Ayberk Yarkın Prabhu, Nishanth Marer Gordon, Cameron |
| contents | We empirically show that process-based Parallelism speeds up the Genetic Algorithm (GA) for Feature Selection (FS) 2x to 25x, while additionally increasing the Machine Learning (ML) model performance on metrics such as F1-score, Accuracy, and Receiver Operating Characteristic Area Under the Curve (ROC-AUC). |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_10846 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Distributed Genetic Algorithm for Feature Selection Potter, Michael Yıldız, Ayberk Yarkın Prabhu, Nishanth Marer Gordon, Cameron Distributed, Parallel, and Cluster Computing We empirically show that process-based Parallelism speeds up the Genetic Algorithm (GA) for Feature Selection (FS) 2x to 25x, while additionally increasing the Machine Learning (ML) model performance on metrics such as F1-score, Accuracy, and Receiver Operating Characteristic Area Under the Curve (ROC-AUC). |
| title | Distributed Genetic Algorithm for Feature Selection |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2401.10846 |