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6. (10 pts) Consider two tree-based methods, Bagging and Random Forests. (a) (b pts) How does Bagging a regression tree differ from a Random Forests?

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6. (10 pts) Consider two tree-based methods, Bagging and Random Forests. (a) (b pts) How does Bagging a regression tree differ from a Random Forests? Why might Random Forests be preferable? (b) (5 pts) When we apply Bagging to decision trees, or when we construct Random Forests, each tree fit to a different bootstrap replicate of the data can be grown \"deep\

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