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Prediction and feature selection of low birth weight using machine learning algorithms
13
Zitationen
2
Autoren
2024
Jahr
Abstract
The study reveals Wrapper method as the optimal feature selection technique. The ML method outperforms traditional methods, with Random Forest (RF) being the most effective predictive model for Low-Birth-Weight prediction. The study suggests that policymakers in Bangladesh can mitigate low birth weight newborns by considering identified risk factors.
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