Ensemble modeling is a machine learning technique that combines multiple individual models to produce a single, more accurate predictive model. By aggregating the predictions of these diverse models, ensemble methods reduce the risk of overfitting and improve performance on various tasks. This approach is particularly beneficial in fields that require reliable predictions, such as inventory management and logistics planning, where it can optimize stock levels and forecast demand more effectively.
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