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Ensemble learning

Ensemble learning is a machine learning technique that combines multiple machine learning algorithms to produce one predictive model. The idea is that when you combine several "weak learners," they can become "strong learners." Ensemble learning can improve predictive performance and accuracy compared to a single model. Ensemble learning can also reduce the risk of overfitting and underfitting by balancing the trade-off between bias and variance and using different subsets and features of the data.