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This research analyzes food security using the FoodAPS dataset, focusing on household-level data. Employing regression modeling, decision trees, and clustering techniques, it identifies patterns, actionable insights, and profiles. The study addresses public health relevance, highlights access barriers, and provides policy recommendations. Current updates include project adjustments, solutions to challenges, and ongoing assessment through the CRISP-DM framework to ensure effective decision-...