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Discuss the impact of model complexity on ensemble learning. How does the complexity of base models affect the performance of bagging, boosting, and stacking?
A
Complex base models improve performance in bagging by reducing variance, in boosting by reducing bias, and in stacking by combining diverse predictions.
B
Complex base models increase model complexity and reduce performance in all ensemble methods.
C
Complex base models are not relevant for ensemble methods. All methods rely on simple, low-complexity models.
D
Complex base models are only relevant for stacking. Bagging and boosting do not benefit from complex base models.
