Distributed Genetic Algorithm for Feature Selection
Published in arXiv (Cornell University) • Jan 19, 2024
NobleIDNI1P93W95R50S05
Authors:,,
Michael Potter
Ayberk yarkin Yildiz
Nishanth Marer Prabhu
Abstract
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 (R...
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