Instruction: Describe the concept of ensemble learning and provide examples of ensemble methods.
Context: This question tests the candidate's understanding of ensemble learning techniques and their benefits in improving model performance.
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The way I'd explain it in an interview is this: Ensemble learning means combining the predictions of multiple models so the final system is usually more accurate or more stable than any one model alone. The intuition is that different models make different mistakes, and combining them can...
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