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The paper discusses the integration of machine learning techniques, specifically Logistic Regression, Decision Trees, and Random Forest algorithms, into online subsidy management systems to enhance efficiency and transparency in government subsidy programs. It highlights the challenges of traditional systems and the potential of machine learning for automating eligibility assessments, fraud detection, and optimizing policy outcomes. The review serves as a reference for researchers and policymakers aiming to

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Movies

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