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Discuss the role of hyperparameter tuning in ensemble learning. How does hyperparameter tuning affect the performance of bagging, boosting, and stacking?
A
Hyperparameter tuning improves performance in bagging by reducing variance, in boosting by reducing bias, and in stacking by balancing predictions.
B
Hyperparameter tuning does not affect the performance of ensemble methods. All methods rely on default hyperparameters.
C
Hyperparameter tuning increases model complexity and reduces performance in all ensemble methods.
D
Hyperparameter tuning is only relevant for stacking. Bagging and boosting do not benefit from hyperparameter tuning.
