Ensemble Methods Interview Questions
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Ensemble methods are widely employed in machine learning to improve prediction accuracy, reduce overfitting, and enhance the robustness of models.
By combining multiple individual models into a unified ensemble, ensemble methods harness the collective wisdom of diverse learners to make more accurate and reliable predictions. In this article, we delve into the reasons why ensemble methods are used extensively in various domains and highlight their benefits and applications.