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When to use ensemble learning?
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Answer / Rajesh Kushwaha
Ensemble Learning is typically used in the following scenarios: (1) When there are many noisy or redundant features in the data; (2) When the dataset is small, and a single model may not capture all patterns; (3) When the goal is to improve the robustness of predictions, especially for real-world applications where errors can have serious consequences.
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