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In a scenario where you have a large number of weakly correlated features, how can ensemble techniques help improve the performance of your machine learning model?
A
Use feature selection techniques to select a subset of the most relevant features before training the ensemble models.
B
Train multiple models in the ensemble using different subsets of features, allowing each model to focus on different aspects of the data.
C
Use dimensionality reduction techniques like PCA to reduce the number of features before training the ensemble models.
D
All of the above
