Applying XGBoost, Neural Networks, and Oversampling in the Undernutrition Classification of School-Aged Children in the Philippines

• المؤلفون الرئيسيون: Yiu, Mark Kevin A.Ong, Pastor, Carlo Gabriel M., Candano, Gabrielle Jackie C., Miro, Eden Delight, Antonio, Victor Andrew A., Go, Clark Kendrick C
• التنسيق: text
• منشور في: Archīum Ateneo 2024
• الموضوعات: Applied Mathematics; Data Science
• الوصول للمادة أونلاين: https://archium.ateneo.edu/mathematics-faculty-pubs/301; https://doi.org/10.1063/5.0213404

In the Philippines, one in five school-aged children are affected by undernutrition, increasing their risk of physical and cognitive development. The Department of Education (DepEd) attempts to address this issue by targeting children with low body mass index (BMI) for their school-based feeding pro...