Ensemble learning

Ensemble learning is a technique where multiple machine learning models work together to make predictions, similar to how a panel of experts might combine their opinions to reach a better conclusion than any single expert could alone. By training different models on the same data or using variations of the same algorithm, scientists can blend their predictions to reduce errors and improve accuracy. This approach often produces more reliable and robust results than relying on a single model, making it a powerful tool for everything from medical diagnosis to weather forecasting.