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IEEE/ICACT20250097 Slide.10        [Big Slide]	Oral Presentation
	Random Forest is an ensemble learning technique that combines multiple decision trees to improve accuracy and reduce overfitting. It performs well with nonlinear data. It is more robust than linear models but can still struggle with highly volatile economic variables. XGBoost is a boosting algorithm known for its efficiency and high performance in predictive modeling. It optimizes forecasting by sequentially improving weak models. Our study found that XGBoost outperforms other models in predicting GDP, inflation, unemployment, and exchange rates.

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