Explainable Machine Learning for Classifying Iron–Folic Acid Supplementation Adherence Among Pregnant Women Attending Antenatal Care in Bosaso, Somalia: Dataset and Supporting Materials IFAS Adherence Machine Learning Dataset

This dataset and supporting materials accompany a facility-based cross-sectional study of iron–folic acid supplementation (IFAS) adherence among 400 pregnant women attending antenatal care at Bosaso General Hospital and Boqolka Buush MCH Center, Bosaso, Somalia. The record contains de-identified study data and materials used for machine-learning analyses comparing eight supervised classification algorithms and SHAP-based model interpretation.