Ensemble Modeling Techniques

Ensemble modeling combines multiple individual models to improve overall prediction accuracy. Think of it like consulting several experts and trusting the majority opinion, rather than relying on just one. Each model analyzes data differently, and by merging their outputs—using methods like averaging or voting—the ensemble reduces errors and compensates for individual weaknesses. This approach often yields more reliable and robust results than any single model alone. Ensemble techniques are widely used in fields like finance, healthcare, and machine learning to make better predictions and decisions.