muhammadsalek/SBA-Zambia-ML-Analysis

Code and analysis for identifying key determinants and province-level disparities of skilled birth attendance in Zambia using machine learning on complex survey data. # SBA-Zambia-ML-Analysis Code and analysis for identifying key determinants and province-level disparities of skilled birth attendance in Zambia using machine learning on complex survey data. This repository contains all code, figures, and tables for the study: Identifying Key Determinants and Geographic Inequities of Skilled Birth Attendance in Zambia Using Machine Learning on Complex Survey Data The study uses secondary data from the 2024 Zambia Demographic and Health Survey (ZDHS) and applies supervised machine learning and spatial analysis to identify key determinants of Skilled Birth Attendance (SBA) and geographic disparities across provinces. # Key Outputs # Tables performance.csv → ML model performance metrics tuned_performance.csv → Hyperparameter-tuned model performance # Figures Rplot01.tiff → Feature importance plot Rplot02.tiff → Province-level SBA coverage map Rplot03.tiff – Rplot17.tiff → Additional ML and spatial analysis figures Note: Raw ZDHS data cannot be shared due to privacy agreements. Use synthetic/sample data to test scripts. # Contact Md Salek Miah – saleksta@gmail.com Md Jamal Uddin – jamal-sta@sust.edu