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Discuss the advantages and disadvantages of stacking in ensemble learning. Provide a scenario where stacking would be the most effective ensemble method.
A
Stacking combines predictions from multiple models, improving performance but increasing complexity. Stacking is effective in scenarios with diverse models and complex relationships.
B
Stacking reduces variance but increases bias. Stacking is effective in scenarios with high variance.
C
Stacking is not effective in improving model performance. It increases model complexity without significant benefits.
D
Stacking is identical to bagging and boosting. It has no specific advantages or disadvantages.
