Distributed Genetic Algorithm for Feature Selection Article Swipe
Related Concepts
Receiver operating characteristic
Feature selection
Selection (genetic algorithm)
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Process (computing)
Artificial intelligence
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Parallelism (grammar)
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Pattern recognition (psychology)
Parallel computing
Operating system
Philosophy
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Michael Potter
,
Ayberk yarkin Yildiz
,
Nishanth Marer Prabhu
,
Cameron Gordon
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2401.10846
· OA: W4391124821
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2401.10846
· OA: W4391124821
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).
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